PACK_ID: CIVOS_PACK_HCCP_01
NAME: Hidden Control & Coordination Primitives (HCCP)
VERSION: v1.0
APPLIES: Z0–Z6, P0–P3
DEPENDENCIES: FenceOS, ERCO, ChronoHelmAI, Phase×Zoom, AVOO Role Lattice
PRIMITIVES (State Variables)
B(t): BeliefState (what we think is true)
H(t): HiddenState (what is true but unobserved)
O(t): Observability (coverage, latency, bias)
R(t): SharedReality (coherence + legitimacy)
A(t): ActuationCapacity (enforcement throughput + latency)
I(t): IncentiveField (reward gradients shaping behavior)
G: CapabilityGraph (dependency DAG + bottlenecks + diffusion)
X(t): ExternalityLedger (exported/hidden costs; deferred load)
T: TopologyGraph (routes, chokepoints, redundancy)
M(t): MultiActorGameState (commitments, reputations, escalation ladders)
MASTER LAW (Operational Rate Dominance)
Ġ_effective(t) = Ġ_true(t)
  − L_obs(t)   − L_reality(t) − L_act(t) − L_incent(t)
  − L_bottle(t)− L_ext(t)     − L_topo(t)− L_game(t)
STABILITY CONDITION (Phase Envelope)
Ġ_effective(t) ≥ Ḋ(t)
If violated persistently → P2→P1 drift; if TTC collapses → P1→P0 fracture.

ERCO_LOOP:
1) Read SENSOR_DICT (all modules)
2) Check THRESHOLDS (per module)
3) Choose REPAIR_ACTIONS (truncate / stitch / localize / redesign)
4) Schedule WINDOWS via ChronoHelmAI:
   - FREEZE window (Operator stability)
   - SANDBOX window (Architect exploration)
   - DEPLOY window (rollout)
5) Retest cadence + exit conditions

FENCE_TRIGGER_TEMPLATE:
TriggerCondition: <sensor crossing or combined predicate>
Actuation:
  - FREEZE (stop unstable changes)
  - PROBE (improve observability)
  - LOCALIZE (reduce coupling)
  - AUDIT (counter-signal)
  - REDESIGN (incentives/mechanisms/topology)
Retest:
  - what to measure
  - cadence
ExitCondition:
  - return inside safe band (P-upgrade corridor)

ModuleID: CIVOS_MODULE_OBSOS_01
Name: OBSOS (Observability & Hidden-State Layer)
Type: Runtime primitive
Applies: Z0–Z6, P0–P3
OwnerRoles: ORC primary, OPR execution, ARC red-team
Contract:
- Maintain B(t) about H(t) using noisy signals.
- Detect blindspots + deception.
- Output belief intervals, not fake certainty.
Inputs:
- SENSOR_STREAM_ALL
- SIGNAL_QUALITY {coverage, latency, bias, sampling_rate}
- ADVERSARY_MODEL (optional)
Outputs:
- POSTERIOR_RISK_DISTS
- FOG_MAP (blind regions)
- DECEPTION_ALERTS
- SURPRISE_BUDGET
Sensors:
- OBS_COVERAGE ∈ [0,1]
- SIGNAL_LATENCY Δt
- BIAS_INDEX
- DECEPTION_INDEX
- SURPRISE_RATE = d(|prediction_error|)/dt
Thresholds → FenceOS:
- If OBS_COVERAGE < θ_cov AND SURPRISE_RATE > θ_sur:
    FENCE: FREEZE + PROBE (increase coverage, reduce latency)
- If DECEPTION_INDEX > θ_dec:
    FENCE: AUDIT + COUNTER_SIGNAL + RED_TEAM
Failure trace:
Low observability → B≠H → false stability → delayed repair → TTC collapses → P2→P1→P0.

ModuleID: CIVOS_MODULE_REALITYOS_01
Name: REALITYOS (Shared Reality & Legitimacy Substrate)
Type: Runtime primitive
Applies: Z0–Z6, P0–P3
OwnerRoles: ORC + GOV lattice nodes
Contract:
- Treat shared reality as load-bearing infrastructure.
- Track fragmentation, trust decay, irreversibility crossings.
Inputs:
- LANGUAGE_SIGNALS (institutional comms, education outputs, media)
- TRUST_SIGNALS (compliance, participation, churn)
- COHERENCE_SIGNALS (contradiction rate, rumor saturation)
Outputs:
- SHARED_REALITY_SCORE
- LEGITIMACY_SCORE
- IRREVERSIBILITY_STATUS (approaching/crossed)
- REPAIR_CORRIDORS
Sensors:
- SHARED_REALITY_GAP (between groups)
- TRUST_DECAY_RATE
- CONTRADICTION_DENSITY
- MEME_R0 (destabilizing spread)
- NIT (Irreversibility Threshold sensor)
Thresholds → FenceOS / AVOO:
- If IRREVERSIBILITY_STATUS = crossed:
    FENCE: CONTAIN + LOCALIZE + CORRIDOR_REPAIR
- If TRUST_DECAY_RATE > θ_trust:
    AVOO: reduce Operator choice injection; stabilize SOP
Failure trace:
Reality split → coordination cost spike → enforcement overuse → legitimacy erosion → compliance collapse → P1/P0.

ModuleID: CIVOS_MODULE_ACTOS_01
Name: ACTOS (Actuation & Enforcement Capacity)
Type: Runtime primitive
Applies: Z0–Z6
OwnerRoles: OPR primary, ORC thresholds, ARC alternatives
Contract:
- Rules do not execute themselves.
- Model enforcement as finite throughput with latency + legitimacy cost.
Inputs:
- RULESET
- INCIDENT_STREAM
- RESOURCE_BUDGET (people/time/tools)
- PROCEDURE_SET (due process)
Outputs:
- ACTUATION_PLAN
- LATENCY_EST
- LEGITIMACY_DAMAGE_EST
- PRIORITIZATION (enforce vs redesign)
Sensors:
- T_ENFORCE
- ENFORCEMENT_THROUGHPUT
- COST_ENFORCE
- EVASION_RATE
- LEGITIMACY_DAMAGE_RATE
Thresholds → FenceOS:
- If T_ENFORCE > θ_time AND EVASION_RATE rising:
    switch to INCOS+CAPOS structural repair (don’t brute-force)
- If LEGITIMACY_DAMAGE_RATE > θ_leg:
    FENCE: STOP_LOSS (reduce intensity, increase transparency)
Failure trace:
Slow actuation → violations normalize → spike enforcement → legitimacy damage → compliance loss → P0.

ModuleID: CIVOS_MODULE_INCOS_CAPOS_01
Name: INCOS+CAPOS (Incentives & Capture Control)
Type: Runtime primitive
Applies: Z0–Z6
OwnerRoles: ORC primary, OPR execution, ARC redesign
Contract:
- Incentives are a field that bends behavior.
- Detect capture, rent-seeking, and metric gaming as structural drift.
Inputs:
- PAYOFFS (money/status/promotion/penalties)
- OUTCOME_METRICS (public + private)
- NETWORK_EDGES (who benefits)
- ALLOCATIONS / PROCUREMENT (where relevant)
Outputs:
- INCENTIVE_ALIGNMENT_SCORE
- CAPTURE_INDEX
- MECHANISM_PATCHES
- ANTI_GOODHART_PLAN
Sensors:
- PRINCIPAL_AGENT_GAP
- RENT_SEEK_RATE
- CAPTURE_INDEX
- GOODHART_PRESSURE
Thresholds → FenceOS:
- If CAPTURE_INDEX > θ_cap:
    FENCE: FREEZE allocations + ROTATE roles + AUDIT binds
- If GOODHART_PRESSURE > θ_gh:
    switch sensors: multi-metric + randomized audits
Failure trace:
Metric becomes target → gaming rises → Ġ_true falls → dashboard lies → delayed repair → P1/P0.

ModuleID: CIVOS_MODULE_CAPGRAPHOS_01
Name: CAPGRAPHOS (Capability Graph & Bottlenecks)
Type: Runtime primitive
Applies: Z0–Z6
OwnerRoles: ORC maps DAG; EDU executes regen pipelines
Contract:
- Model capability as dependency DAG with bottlenecks + diffusion delays.
- Identify single points of failure (SPOFs).
Inputs:
- CAPABILITY_NODES
- DEPENDENCY_EDGES
- TRAINING_PIPELINES (EducationOS)
- TRANSFER_CHANNELS (trade/migration/learning)
Outputs:
- BOTTLENECK_LIST (ranked)
- SPOF_NODE_LIST
- DIFFUSION_EST
- UPSTREAM_REPAIR_PLAN
Sensors:
- BOTTLENECK_CRITICALITY
- DEPENDENCY_DEPTH
- DIFFUSION_HALF_LIFE
- SPOF_COUNT
- TRAINING_THROUGHPUT
Thresholds → ERCO/FenceOS:
- If BOTTLENECK_CRITICALITY > θ_bn:
    ERCO: prioritize upstream training/repair
- If SPOF risk high:
    FENCE: build redundancy (duplicate pipeline)
Failure trace:
Hidden bottleneck → throughput caps → load rises → cascade → sudden P0.

ModuleID: CIVOS_MODULE_EXLEDGEROS_01
Name: EXLEDGEROS (Externality & Deferred Load Ledger)
Type: Runtime primitive
Applies: Z0–Z6
OwnerRoles: ORC + FIN/GOV/ENV lanes
Contract:
- Track exported costs and deferred damage that fake stability.
- Convert hidden debt into future Ḋ(t) projections.
Inputs:
- COST_EXPORT_SIGNALS
- DEFERRED_MAINTENANCE
- SPILLOVER_SIGNALS (env/health/social) where available
Outputs:
- EXTERNALITY_LOAD
- DEBT_SERVICE_FORECAST (future damage rate)
- TRUE_NET_REGEN_EST
Sensors:
- EXTERNALITY_LOAD
- DEFERRED_DAMAGE_RATE
- MAINTENANCE_BACKLOG
- TRUE_NET_REGEN = Ġ_true − debt_service
Thresholds → FenceOS:
- If DEFERRED_DAMAGE_RATE > θ_def:
    FENCE: truncate growth; prioritize repair
- If TRUE_NET_REGEN < Ḋ:
    enter recovery corridor (P-upgrade plan)
Failure trace:
Externalise → false surplus → backlog grows → debt service spikes → abrupt fracture.

ModuleID: CIVOS_MODULE_TOPOOS_01
Name: TOPOOS (Topology & Corridor Fragility)
Type: Runtime primitive
Applies: Z0–Z6
OwnerRoles: ARC maps corridors; OPR builds redundancy
Contract:
- Topology sets the feasible set of pipelines.
- Detect chokepoints, fragility, and coupling traps.
Inputs:
- ROUTE_GRAPH (supply/comms/logistics)
- NODE_CRITICALITY
- REDUNDANCY_OPTIONS
Outputs:
- CHOKEPOINT_INDEX
- CORRIDOR_FRAGILITY
- REDUNDANCY_PLAN
- BUFFER_PLACEMENT_PLAN
Sensors:
- CHOKEPOINT_INDEX
- ROUTE_REDUNDANCY
- DISTANCE_FRICTION
- CORRIDOR_FRAGILITY
Thresholds → FenceOS:
- If CHOKEPOINT_INDEX > θ_choke:
    build bypass + local buffers
- If CORRIDOR_FRAGILITY rising:
    localize dependencies (reduce coupling)
Failure trace:
Single corridor → cut → core organs starve → cascade → P0.

ModuleID: CIVOS_MODULE_INTERACTOS_01
Name: INTERACTOS (Interaction & Commitment Control)
Type: Runtime primitive
Applies: Z3–Z6 (can scale down)
OwnerRoles: ORC + GOV/DEF/FIN lanes
Contract:
- Model repeated interactions under misperception.
- Track credible commitment and escalation ladder position.
Inputs:
- ACTOR_LIST
- COMMITMENTS (treaties/deals/promises)
- SIGNALS (public/private)
- CAPABILITY_ESTIMATES (from OBSOS)
Outputs:
- MISPERCEPTION_PROB
- CREDIBLE_COMMITMENT_SCORE
- ESCALATION_LADDER_POSITION
- DE_ESCALATION_CORRIDORS
Sensors:
- MISPERCEPTION_PROB
- COMMITMENT_BREAK_RATE
- RETALIATION_LATENCY
- ESCALATION_LADDER_POSITION
Thresholds → FenceOS / ChronoHelmAI:
- If MISPERCEPTION_PROB > θ_mis:
    increase verification; reduce provocative moves
- If ladder near threshold:
    ChronoHelmAI enforces COOLDOWN window
Failure trace:
Misperception → overreaction → escalation → damage spike → fast attrition collapse mode.

INSTALL_ORDER:
1) OBSOS          (truth under fog)
2) REALITYOS      (coordination substrate)
3) ACTOS          (rules execute)
4) INCOS+CAPOS    (incentives don’t rot the system)
5) CAPGRAPHOS     (bottlenecks & diffusion)
6) EXLEDGEROS     (hidden debt)
7) TOPOOS         (corridor fragility)
8) INTERACTOS     (multi-actor escalation control)

CHAIN_ID: CHAIN_SGP_BTM_EDUKATE_v1
COUNTRY:SGP (Z5)
  → CITY:SGP:BTM (Z3)
    → INST:SGP:BTM:EDUKATE (Z2)
      → ROLESET:AVOO (Z1)
        → IND:* (Z0 anonymised individuals)
Edge types:
- HAS_CITY
- HAS_INSTITUTION
- HAS_ROLESET
- SERVES (INST → IND)
- TRAINS (INST → IND)
- MEASURES (INST → SENSORPACK)
- GOVERNS (COUNTRY/CITY → RULESET)

SENSORPACK_ID: SENSORPACK_HCCP_MIN_v1
SENSORS:
- OBSOS: OBS_COVERAGE, SIGNAL_LATENCY, DECEPTION_INDEX, SURPRISE_RATE
- REALITYOS: SHARED_REALITY_GAP, TRUST_DECAY_RATE, CONTRADICTION_DENSITY, NIT
- ACTOS: T_ENFORCE, EVASION_RATE, LEGITIMACY_DAMAGE_RATE
- INCOS+CAPOS: CAPTURE_INDEX, GOODHART_PRESSURE, RENT_SEEK_RATE
- CAPGRAPHOS: BOTTLENECK_CRITICALITY, SPOF_COUNT, TRAINING_THROUGHPUT
- EXLEDGEROS: MAINTENANCE_BACKLOG, DEFERRED_DAMAGE_RATE, TRUE_NET_REGEN
- TOPOOS: CHOKEPOINT_INDEX, ROUTE_REDUNDANCY, CORRIDOR_FRAGILITY
- INTERACTOS (Z3+): MISPERCEPTION_PROB, ESCALATION_LADDER_POSITION

RUN_ID: RUN_SGP_BTM_EDU_001
Observed:
- OBS_COVERAGE low (θ_cov violated) + SURPRISE_RATE rising
Inference:
- B(t) likely diverging from H(t): false stability risk
Action:
- FenceOS: FREEZE new changes
- OBSOS: PROBE (increase coverage, shorten latency)
- ERCO: schedule retest in 7 days
Exit:
- OBS_COVERAGE above θ_cov AND SURPRISE_RATE below θ_sur for 2 cycles

PROMPT_HCCP_RUNNER_v1:
You are CivOS Runtime. Run HCCP Pack v1.0.
Input:
1) PlaceChain (e.g., COUNTRY:SGP → CITY:SGP:BTM → INST:SGP:BTM:EDUKATE)
2) SENSOR_DICT (values + trend)
3) RULESET summary (if any)
4) Current Phase estimate (P0–P3) and Zoom level (Z0–Z6)
Tasks:
A) Run OBSOS: identify blindspots, deception risk, surprise budget.
B) Run REALITYOS: shared reality gap, trust decay, irreversibility status (NIT).
C) Run ACTOS: actuation latency vs TTC, evasion trend, legitimacy damage.
D) Run INCOS+CAPOS: capture index, Goodhart pressure, mechanism drift.
E) Run CAPGRAPHOS: bottlenecks/SPOFs limiting throughput.
F) Run EXLEDGEROS: hidden debt/deferred damage raising future Ḋ(t).
G) Run TOPOOS: chokepoints/corridor fragility & redundancy options.
H) Run INTERACTOS (if Z3+): misperception and escalation ladder.
Output format (strict):
1) Phase×Zoom diagnosis
2) Top 5 risks (each: sensor → threshold → failure trace)
3) FenceOS triggers (if any)
4) ERCO repair plan (truncate/stitch/localize/redesign)
5) ChronoHelmAI schedule windows (Freeze/Sandbox/Deploy)
6) Retest plan + exit conditions

OPERATOR_PANEL_HCCP_v1:
- Truth: OBS_COVERAGE | SIGNAL_LATENCY | SURPRISE_RATE | DECEPTION_INDEX
- Coherence: SHARED_REALITY_GAP | TRUST_DECAY_RATE | NIT_STATUS
- Actuation: T_ENFORCE | EVASION_RATE | LEGITIMACY_DAMAGE_RATE
- Incentives: CAPTURE_INDEX | GOODHART_PRESSURE
- Bottlenecks: BOTTLENECK_CRITICALITY | SPOF_COUNT | TRAINING_THROUGHPUT
- Hidden debt: MAINTENANCE_BACKLOG | TRUE_NET_REGEN
- Topology: CHOKEPOINT_INDEX | ROUTE_REDUNDANCY | CORRIDOR_FRAGILITY
- Interaction (Z3+): MISPERCEPTION_PROB | ESCALATION_LADDER_POSITION

LOCKS:
1) This pack is franchise-free. Names are abstract primitives only.
2) IDs are stable. Do not rename ModuleIDs; only version forward.
3) Every threshold must have:
   - a FenceOS actuation
   - an ERCO repair plan
   - a retest cadence
   - an exit condition
4) Negative-void is mandatory: each module declares the failure trace if missing.

TITLE: CivOS Runtime Add-On Pack — Hidden Control & Coordination Primitives (v1.0)
Slug (suggested): /civos-runtime-hidden-control-primitives-v1-0/
Purpose: Add the missing real-world primitives that make civilisation simulation *actually work* under fog, deception, legitimacy drift, enforcement limits, incentive capture, capability dependencies, externalisation, topology constraints, and multi-actor interaction.
Franchise-free: No references to any specific game/film. Pure systems spec.
VERSIONING
- Runtime Unified Version: CivOS_AddOn_HCCP_v1.0
- Forward-Only: never rename IDs; only version forward (v1.1, v1.2…).
SCHEMA (Almost-Code IDs)
- Grammar: Place×Lane×Zoom×Role×Type×ID
- Example: COUNTRY:SGP × LANE:GOV × Z5 × ROLE:OPR × MODULE × CIVOS_MODULE_OBSOS_01
CORE ADDITIONS (New State Variables)
- B(t): BeliefState (what the system thinks is true)
- H(t): HiddenState (what is true but unobserved)
- O(t): Observability (coverage/latency/bias)
- R(t): SharedReality (coherence + legitimacy)
- A(t): ActuationCapacity (enforcement throughput + latency)
- I(t): IncentiveField (reward gradients shaping behavior)
- G: CapabilityGraph (dependency DAG + bottlenecks + diffusion)
- X(t): ExternalityLedger (exported/hidden costs; deferred load)
- T: TopologyGraph (routes, chokepoints, redundancy)
- M(t): MultiActorGameState (commitments, reputations, deterrence ladder)
MASTER LAW (Operational Rate-Dominance under Hidden Costs)
- Define effective regeneration:
  Ġ_effective(t) =
      Ġ_true(t)
    − L_obs(t)        [loss from observation lag & mis-inference]
    − L_narr(t)       [coordination loss from shared reality fragmentation]
    − L_act(t)        [enforcement overhead + legitimacy damage]
    − L_cap(t)        [capability bottleneck throttling]
    − L_cap2(t)       [capture / incentive gaming leakage]
    − L_ext(t)        [externality debt service / deferred damage]
    − L_topo(t)       [topology friction + chokepoint fragility]
    − L_game(t)       [misperception / escalation / commitment failure]
- Stability condition (Phase envelope):
  Ġ_effective(t) ≥ Ḋ(t)
- If violated persistently → P2→P1 drift; if TTC collapses → P1→P0 fracture.
COUPLING POINTS (Existing CivOS Runtime)
- FenceOS: truncation/stitching actuates when thresholds trip.
- ERCO: reads sensors → chooses repair → schedules retest.
- ChronoHelmAI: schedules repair windows (Freeze/Sandbox/Deploy).
- AVOO: controls choice-budget injection; reduces phase shear.
- Phase×Zoom: every module must be Z0–Z6 compatible; thresholds may vary by Z.
=====================================================================
MODULE 01 — OBSOS (Observability + Fog + Deception)
=====================================================================
ModuleID: CIVOS_MODULE_OBSOS_01
Name: OBSOS (Observability & Hidden-State Layer)
META
- Type: Runtime primitive
- Applies: Z0–Z6, P0–P3
- Owner Roles: ORC (Oracle) primary, OPR (Operator) execution, ARC (Architect) red-team
CONTRACT
- Maintain B(t) (belief) about H(t) (hidden reality) using noisy signals.
- Detect deception, blindspots, and surprise risk.
- Output “belief intervals”, not fake certainty.
INPUTS
- SENSOR_STREAM_ALL
- SIGNAL_QUALITY: {coverage, latency, bias, sampling_rate}
- ADVERSARY_MODEL (optional): {capability, intent, incentives}
OUTPUTS
- POSTERIOR_RISK: distribution over key hazards
- FOG_MAP: where the system is blind
- DECEPTION_ALERTS
- SURPRISE_BUDGET: expected shock absorb capacity before phase drop
SENSORS
- OBS_COVERAGE ∈ [0,1]
- SIGNAL_LATENCY (Δt)
- BIAS_INDEX (systematic error)
- DECEPTION_INDEX (incentive-inconsistent anomalies)
- SURPRISE_RATE = d(|prediction_error|)/dt
THRESHOLDS → FENCE TRIGGERS
- If OBS_COVERAGE < θ_cov AND SURPRISE_RATE > θ_sur → FENCE: FREEZE + PROBE
- If DECEPTION_INDEX > θ_dec → FENCE: AUDIT + COUNTER-SIGNAL + RED-TEAM
PHASE×ZOOM NOTES
- Z0–Z2: often high noise; small shocks can be fatal → tighter θ_sur
- Z5–Z6: coverage gaps hide systemic drift → stronger bias detection
FAILURE TRACE (Non-emotive)
Low observability → B(t)≠H(t) → false stability → delayed repair → TTC collapses → P2→P1→P0.
CHECKLIST
- [ ] Minimum coverage achieved?
- [ ] Latency within TTC?
- [ ] Counter-signal channel exists?
- [ ] Red-team cadence scheduled?
=====================================================================
MODULE 02 — REALITYOS (Shared Reality + Legitimacy + Irreversibility)
=====================================================================
ModuleID: CIVOS_MODULE_REALITYOS_01
Name: REALITYOS (Shared Reality & Legitimacy Substrate)
META
- Type: Runtime primitive
- Applies: Z0–Z6, P0–P3
- Owner Roles: ORC + GOV lattice nodes
CONTRACT
- Treat shared reality as load-bearing infrastructure.
- Track fragmentation, trust decay, and irreversibility threshold crossings.
INPUTS
- LANGUAGE_SIGNALS: statements, education outputs, institutional comms
- TRUST_SIGNALS: compliance, participation, churn, volunteerism
- COHERENCE_SIGNALS: contradiction rate, rumor saturation
OUTPUTS
- SHARED_REALITY_SCORE
- LEGITIMACY_SCORE
- IRREVERSIBILITY_STATUS (approaching / crossed)
- REPAIR_CORRIDORS (what restores coherence fastest)
SENSORS
- SHARED_REALITY_GAP (between groups)
- TRUST_DECAY_RATE
- CONTRADICTION_DENSITY
- MEME_R0 (destabilizing spread rate)
- NIT (Narrative/Reality Irreversibility Threshold sensor)
THRESHOLDS → FENCE TRIGGERS
- If NIT crossed → FENCE: CONTAIN + LOCALIZE + CORRIDOR REPAIR
- If TRUST_DECAY_RATE > θ_trust → AVOO: reduce Operator choice injection (stabilize SOP)
FAILURE TRACE
Reality fragmentation → coordination cost spike → enforcement overuse → legitimacy erosion → compliance collapse → P1/P0.
CHECKLIST
- [ ] Single source of truth exists?
- [ ] Contradiction repair loop exists?
- [ ] Trust sensors monitored weekly?
- [ ] NIT off-ramp corridors defined?
=====================================================================
MODULE 03 — ACTOS (Rule Actuation / Enforcement Capacity)
=====================================================================
ModuleID: CIVOS_MODULE_ACTOS_01
Name: ACTOS (Actuation & Enforcement Supply Chain)
META
- Type: Runtime primitive
- Applies: Z0–Z6
- Owner Roles: OPR (Operator) primary; ORC designs thresholds; ARC designs alternatives
CONTRACT
- Model rules as non-executing text unless actuation capacity exists.
- Track enforcement throughput, latency, evasion, and legitimacy damage.
INPUTS
- RULESET
- INCIDENT_STREAM
- RESOURCE_BUDGET: people/time/tools
- PROCEDURE_SET (due process)
OUTPUTS
- ACTUATION_PLAN
- LATENCY_ESTIMATES
- LEGITIMACY_DAMAGE_EST
- PRIORITIZATION (what to enforce vs what to redesign)
SENSORS
- T_ENFORCE (time to act)
- COST_ENFORCE
- EVASION_RATE
- ENFORCEMENT_THROUGHPUT
- LEGITIMACY_DAMAGE_RATE
THRESHOLDS → FENCE TRIGGERS
- If T_ENFORCE > θ_time AND EVASION rising → switch from force to Incentive repair (Module 04)
- If LEGITIMACY_DAMAGE_RATE > θ_leg → FENCE: STOP-LOSS (reduce intensity; increase transparency)
FAILURE TRACE
Slow actuation → violations normalize → spike enforcement → legitimacy damage → loss of compliance → P0.
CHECKLIST
- [ ] Actuation latency < TTC?
- [ ] Due process intact?
- [ ] Evasion monitored?
- [ ] Structural redesign path exists?
=====================================================================
MODULE 04 — INCOS (Incentive Field) + CAPOS (Capture / Gaming)
=====================================================================
ModuleID: CIVOS_MODULE_INCOS_CAPOS_01
Name: INCOS+CAPOS (Incentives & Capture Control)
META
- Type: Runtime primitive
- Applies: Z0–Z6
- Owner Roles: ORC primary, OPR execution, ARC redesign mechanisms
CONTRACT
- Represent incentives as a field that shapes behavior over time.
- Detect capture (rent-seeking, corruption, metric gaming) as structural drift.
INPUTS
- PAYOFFS: money/status/promotion/penalties
- OUTCOME_METRICS (public + private)
- NETWORK_EDGES: who benefits from what
- PROCUREMENT/ALLOCATIONS (if applicable)
OUTPUTS
- INCENTIVE_ALIGNMENT_SCORE
- CAPTURE_INDEX
- MECHANISM_PATCHES (rule changes)
- ANTI-GOODHART_PLAN (sensor redesign + audits)
SENSORS
- PRINCIPAL_AGENT_GAP
- RENT_SEEK_RATE
- CAPTURE_INDEX (gain concentration vs mission)
- GOODHART_PRESSURE (metric gaming probability)
- WHISTLE_SIGNAL_RATE (optional)
THRESHOLDS → FENCE TRIGGERS
- If CAPTURE_INDEX > θ_cap → FENCE: FREEZE allocations + rotate roles + audit binds
- If GOODHART_PRESSURE > θ_gh → switch sensors: multi-metric + randomized audits
FAILURE TRACE
Metric becomes target → gaming rises → Ġ_true falls → dashboard lies → delayed repair → P1/P0.
CHECKLIST
- [ ] Incentives aligned to regeneration?
- [ ] Capture index tracked?
- [ ] Goodhart countermeasures active?
- [ ] Rotation/audit protocol defined?
=====================================================================
MODULE 05 — CAPGRAPHOS (Capability Dependency Graph + Diffusion)
=====================================================================
ModuleID: CIVOS_MODULE_CAPGRAPHOS_01
Name: CAPGRAPHOS (Capability Graph & Bottlenecks)
META
- Type: Runtime primitive
- Applies: Z0–Z6
- Owner Roles: ORC maps dependency DAG; EDU nodes execute regeneration
CONTRACT
- Model capability as a dependency DAG (prereqs, bottlenecks).
- Track diffusion half-life; identify single points of failure (SPOF).
INPUTS
- CAPABILITY_NODES
- DEPENDENCY_EDGES
- TRAINING_PIPELINES (EducationOS)
- TRANSFER_CHANNELS (migration, trade, learning)
OUTPUTS
- BOTTLENECK_LIST (ranked)
- SPOF_TECH_NODES
- DIFFUSION_ESTIMATES
- UPSTREAM_REPAIR_PLAN
SENSORS
- BOTTLENECK_CRITICALITY
- DEPENDENCY_DEPTH
- DIFFUSION_HALF_LIFE
- SPOF_COUNT
- TRAINING_THROUGHPUT
THRESHOLDS → FENCE TRIGGERS
- If BOTTLENECK_CRITICALITY > θ_bn → ERCO: prioritize upstream training/repair
- If SPOF loss risk high → FENCE: redundancy build (duplicate pipelines)
FAILURE TRACE
Hidden bottleneck → throughput caps → load rises → services fail → cascading loss → P1/P0.
CHECKLIST
- [ ] DAG current?
- [ ] Bottlenecks ranked?
- [ ] Redundancy built on SPOFs?
- [ ] Diffusion plan exists?
=====================================================================
MODULE 06 — EXLEDGEROS (Externalisation + Deferred Damage Accounting)
=====================================================================
ModuleID: CIVOS_MODULE_EXLEDGEROS_01
Name: EXLEDGEROS (Externality & Deferred Load Ledger)
META
- Type: Runtime primitive
- Applies: Z0–Z6
- Owner Roles: ORC + FIN/GOV/ENV lanes
CONTRACT
- Track exported costs and deferred damage that make dashboards look stable.
- Convert hidden debt into future Ḋ(t) projections.
INPUTS
- COST_EXPORT_SIGNALS
- DEFERRED_MAINTENANCE
- ENV/HEALTH/SOCIAL spillovers (as available)
OUTPUTS
- EXTERNALITY_LOAD
- DEBT_SERVICE_FORECAST (future damage rate)
- TRUE_NET_REGEN_EST (Ġ_true vs Ġ_effective)
SENSORS
- EXTERNALITY_LOAD
- DEFERRED_DAMAGE_RATE
- MAINTENANCE_BACKLOG
- TRUE_NET_REGEN = Ġ_true − debt_service
THRESHOLDS → FENCE TRIGGERS
- If DEFERRED_DAMAGE_RATE > θ_def → FENCE: truncate growth; prioritize repair
- If TRUE_NET_REGEN < Ḋ → enter Recovery corridor (P-upgrade plan)
FAILURE TRACE
Externalise costs → false surplus → backlog grows → debt service spikes → sudden P0 fracture.
CHECKLIST
- [ ] Ledger exists?
- [ ] Backlog measured?
- [ ] Debt service forecasted?
- [ ] Repair budget protected?
=====================================================================
MODULE 07 — TOPOOS (Topology Constraints: Corridors, Chokepoints, Redundancy)
=====================================================================
ModuleID: CIVOS_MODULE_TOPOOS_01
Name: TOPOOS (Topology & Corridor Fragility)
META
- Type: Runtime primitive
- Applies: Z0–Z6
- Owner Roles: ARC maps corridors; OPR builds redundancy
CONTRACT
- Treat physical/network topology as constraint fields.
- Detect chokepoints and corridor fragility.
INPUTS
- ROUTE_GRAPH (supply, comms, logistics)
- NODE_CRITICALITY
- REDUNDANCY_OPTIONS
OUTPUTS
- CHOKEPOINT_INDEX
- CORRIDOR_FRAGILITY
- REDUNDANCY_PLAN
SENSORS
- CHOKEPOINT_INDEX
- ROUTE_REDUNDANCY
- DISTANCE_FRICTION
- CORRIDOR_FRAGILITY
THRESHOLDS → FENCE TRIGGERS
- If CHOKEPOINT_INDEX > θ_choke → build bypass routes or local buffers
- If CORRIDOR_FRAGILITY rising → localize dependencies (reduce coupling)
FAILURE TRACE
Single corridor → shock cuts route → core organs starve → cascading failure → P0.
CHECKLIST
- [ ] Chokepoints known?
- [ ] Buffers prepositioned?
- [ ] Redundant corridors built?
- [ ] Coupling reduced where fragile?
=====================================================================
MODULE 08 — INTERACTOS (Multi-Actor Interaction: Commitment, Deterrence, Escalation)
=====================================================================
ModuleID: CIVOS_MODULE_INTERACTOS_01
Name: INTERACTOS (Multi-Actor Interaction & Commitment)
META
- Type: Runtime primitive
- Applies: Z3–Z6 primarily (but can scale down)
- Owner Roles: ORC + GOV/DEF/FIN lanes
CONTRACT
- Model repeated interactions under misperception.
- Track credible commitment, deterrence position, escalation ladders.
INPUTS
- ACTOR_LIST
- COMMITMENTS (treaties, deals, promises)
- SIGNALS (public/private)
- CAPABILITY_ESTIMATES (from OBSOS)
OUTPUTS
- MISPERCEPTION_PROB
- CREDIBLE_COMMITMENT_SCORE
- ESCALATION_LADDER_POSITION
- DE-ESCALATION_CORRIDORS
SENSORS
- MISPERCEPTION_PROB
- COMMITMENT_BREAK_RATE
- RETALIATION_LATENCY
- ESCALATION_LADDER_POSITION
THRESHOLDS → FENCE TRIGGERS
- If MISPERCEPTION_PROB > θ_mis → increase verification; reduce provocative actions
- If ladder position near threshold → force cooldown window (ChronoHelmAI scheduling)
FAILURE TRACE
Misperception → overreaction → escalation → damage rate spike → fast attrition collapse mode.
CHECKLIST
- [ ] Verification channels exist?
- [ ] Ladder positions monitored?
- [ ] Cooldown windows enforced?
- [ ] Credible commitments maintained?
=====================================================================
INSTALL ORDER (Recommended)
=====================================================================
1) CIVOS_MODULE_OBSOS_01          (truth under fog)
2) CIVOS_MODULE_REALITYOS_01      (coordination substrate)
3) CIVOS_MODULE_ACTOS_01          (rules actually execute)
4) CIVOS_MODULE_INCOS_CAPOS_01    (incentives don’t rot the system)
5) CIVOS_MODULE_CAPGRAPHOS_01     (capability bottlenecks)
6) CIVOS_MODULE_EXLEDGEROS_01     (hidden debt)
7) CIVOS_MODULE_TOPOOS_01         (corridor fragility)
8) CIVOS_MODULE_INTERACTOS_01     (multi-actor escalation control)
=====================================================================
RUNTIME INTEGRATION HOOKS (ERCO / FenceOS / ChronoHelmAI)
=====================================================================
ERCO (Read→Decide→Repair→Retest)
- Reads: all sensors above
- Decides: repair corridor selection (truncate vs stitch)
- Schedules: Freeze/Sandbox/Deploy windows (ChronoHelmAI)
- Enforces: FenceOS triggers when thresholds trip
FenceOS Trigger Template (standardized)
- TriggerCondition: sensor crossing
- Actuation: Freeze / Probe / Localize / Audit / Redesign
- Retest: cadence & success criteria
- ExitCondition: return into safe band (P-upgrade)
=====================================================================
MINIMAL PUBLIC SUMMARY (for top of article)
=====================================================================
This pack makes CivOS “real-world runnable” by adding:
- Observability (truth under fog),
- Shared reality (coherence/legitimacy),
- Actuation (enforcement capacity),
- Incentives (capture/gaming control),
- Capability DAG (bottlenecks & diffusion),
- Externality ledger (hidden debt),
- Topology constraints (chokepoints),
- Multi-actor interaction (commitment/escalation).
END PACK

TITLE: [PlaceName] CivOS Deep Dive — Z3→Z0 Directory (v1.0)
Slug: /civos-[place]-deep-dive-z3-z0-v1-0/
Runtime: CivOS_Runtime v1.x + HCCP v1.0
Applies: Z3 city → Z2 district → Z1 institutions → Z0 individuals (anonymised)
Sections:
A) Summary (AI Mode)
B) Definition Lock
C) PlaceChain
D) Node Records (Z3/Z2/Z1/Z0)
E) Edge Records (Binds)
F) Installed Modules + SensorPacks
G) Thresholds + Fence Triggers
H) ERCO Runbook + ChronoHelmAI Windows
I) Failure Traces (minimal, non-emotive)
J) LLM Runner Prompt Block

PACK_ID: CIVOS_PLACE_DEEPDIVE_TEMPLATE_01
VERSION: v1.0
GRAMMAR: Place×Lane×Zoom×Role×Type×ID (forward-only, no renames)
Z-LEVELS (canonical)
- Z3: CITY
- Z2: DISTRICT / NEIGHBOURHOOD
- Z1: INSTITUTION (execution orgs)
- Z0: IND (anonymised individuals / atomic roles)
PHASE LEVELS
- P0: fracture / non-functional under load
- P1: unstable / repeated failures
- P2: stabilizing / repair works but fragile
- P3: stable band / resilient under variation

CHAIN_ID: CHAIN_<COUNTRY>_<CITY>_<DISTRICT>_<INST>_v1
COUNTRY:<ISO3> (Z5 optional; include if used)
  → CITY:<ISO3>:<CITYCODE> (Z3)
    → DISTRICT:<ISO3>:<CITYCODE>:<DISTRICTCODE> (Z2)
      → INST:<ISO3>:<CITYCODE>:<DISTRICTCODE>:<INSTCODE> (Z1)
        → ROLESET:AVOO (Z1)
          → IND:* (Z0 anonymised)

NODE_RECORD_TEMPLATE_v1:
NodeID:
Type: (COUNTRY/CITY/DISTRICT/INST/ROLESET/IND)
ZoomZ: (Z0..Z6)
PhaseP: (P0..P3) [estimate + confidence]
LaneSet: [EDU/GOV/FIN/HLTH/…]
OwnerRoles: [ARC/VIS/ORC/OPR] (who must act)
Contract:
  Inputs:
  Outputs:
Core Pipelines (RePOC-aligned):
  - RegenPipeline:
  - MaintenancePipeline:
  - CoordinationPipeline:
Buffers:
  - Slack:
  - Redundancy:
  - TimeBuffer (TTC):
Installed Modules:
  - FenceOS: (yes/no)
  - ERCO: (yes/no)
  - ChronoHelmAI: (yes/no)
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS, INTERACTOS]
SensorPacks:
  - SENSORPACK_IDs
Notes:
  - Version locks / local assumptions

EDGE_RECORD_TEMPLATE_v1:
EdgeID:
FromNode:
ToNode:
EdgeType: (HAS_CHILD / RUNS / SERVES / TRAINS / GOVERNS / FUNDS / MEASURES / DEPENDS_ON / ROUTES_THROUGH / ENFORCES)
Weight: (0..1) [bind strength]
Latency: (Δt)
Contract:
  - What flows along this edge? (people/info/resources/authority)
  - Failure if severed:
  - Repair actions:

SENSORPACK_TEMPLATE_v1:
SensorPackID:
AppliesToNode:
UpdateCadence: (daily/weekly/monthly/event-driven)
Sensors:
  - <SENSOR_NAME>: value, trend, unit, source
Minimum HCCP set:
  OBSOS: OBS_COVERAGE, SIGNAL_LATENCY, DECEPTION_INDEX, SURPRISE_RATE
  REALITYOS: SHARED_REALITY_GAP, TRUST_DECAY_RATE, CONTRADICTION_DENSITY, NIT
  ACTOS: T_ENFORCE, EVASION_RATE, LEGITIMACY_DAMAGE_RATE
  INCOS+CAPOS: CAPTURE_INDEX, GOODHART_PRESSURE, RENT_SEEK_RATE
  CAPGRAPHOS: BOTTLENECK_CRITICALITY, SPOF_COUNT, TRAINING_THROUGHPUT
  EXLEDGEROS: MAINTENANCE_BACKLOG, DEFERRED_DAMAGE_RATE, TRUE_NET_REGEN
  TOPOOS: CHOKEPOINT_INDEX, ROUTE_REDUNDANCY, CORRIDOR_FRAGILITY
  INTERACTOS (Z3+): MISPERCEPTION_PROB, ESCALATION_LADDER_POSITION

THRESHOLD_TABLE_TEMPLATE_v1:
ThetaID: THETA_<MODULE>_<SENSOR>_01
Condition: <inequality>
PhaseRisk: (P2→P1 / P1→P0)
FenceTrigger:
  - Actuation: FREEZE / PROBE / LOCALIZE / AUDIT / REDESIGN
  - OwnerRole: (OPR/ORC/ARC)
  - RetestCadence:
ExitCondition:
  - <sensor back inside band for N cycles>

ERCO_RUNBOOK_TEMPLATE_v1:
RUN_ID:
Inputs:
  - PlaceChain
  - SENSOR_DICT
  - Current PhaseP estimate
Steps:
1) Diagnose (Phase×Zoom)
2) Select risk top-5 (sensor→threshold→failure trace)
3) Fence actions (immediate stop-loss)
4) Repair plan (truncate/stitch/localize/redesign)
5) ChronoHelmAI schedule:
   - FREEZE window
   - SANDBOX window
   - DEPLOY window
6) Retest plan + exit criteria
Outputs:
  - Updated PhaseP estimate + confidence

CHAIN_ID: CHAIN_SGP_SGP_BTM_EDUKATE_v1
COUNTRY:SGP (Z5)
  → CITY:SGP:SGP (Z3)
    → DISTRICT:SGP:SGP:BTM (Z2)
      → INST:SGP:SGP:BTM:EDUKATE (Z1)
        → ROLESET:AVOO (Z1)
          → IND:ANON:* (Z0)

NodeID: COUNTRY:SGP
Type: COUNTRY
ZoomZ: Z5
PhaseP: P2 (confidence: medium)
LaneSet: [GOV, EDU, FIN, HLTH]
OwnerRoles: [ORC, OPR, ARC]
Contract:
  Inputs: global shocks, trade, migration, information flows
  Outputs: national rule execution, funding, nationwide pipelines
Core Pipelines:
  - RegenPipeline: EducationOS (capability regeneration)
  - MaintenancePipeline: institutional continuity + staffing
  - CoordinationPipeline: shared reality + enforcement + incentives
Buffers:
  - Slack: policy/fiscal/time buffers
  - Redundancy: multi-route supply + multi-institution education paths
  - TimeBuffer (TTC): national TTC to irreversible failure
Installed Modules:
  - FenceOS: yes
  - ERCO: yes
  - ChronoHelmAI: yes
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS, INTERACTOS]
SensorPacks:
  - SENSORPACK_SGP_Z5_HCCP_MIN_v1
Notes:
  - CITY is also national-scale (city-state); keep both nodes for graph consistency.

NodeID: CITY:SGP:SGP
Type: CITY
ZoomZ: Z3
PhaseP: P2 (confidence: medium)
LaneSet: [EDU, GOV, FIN, HLTH]
OwnerRoles: [OPR, ORC, ARC]
Contract:
  Inputs: district data, infra/logistics corridors, population flows
  Outputs: city-wide routing, district support, execution standards
Core Pipelines:
  - RegenPipeline: city education ecosystem + teacher/tutor capacity
  - MaintenancePipeline: staffing continuity, coordination costs control
  - CoordinationPipeline: shared reality + enforcement timing + incentives
Buffers:
  - Slack: spare capacity in schools/tutors/services
  - Redundancy: cross-district options + backup pipelines
  - TTC: city TTC to service collapse / safety incidents
Installed Modules:
  - FenceOS: yes
  - ERCO: yes
  - ChronoHelmAI: yes
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS, INTERACTOS]
SensorPacks:
  - SENSORPACK_SGP_CITY_Z3_HCCP_MIN_v1
Notes:
  - City is where corridor fragility (TOPOOS) shows up early.

NodeID: DISTRICT:SGP:SGP:BTM
Type: DISTRICT
ZoomZ: Z2
PhaseP: P2→P3 (confidence: low-to-medium; depends on lane)
LaneSet: [EDU, GOV]
OwnerRoles: [OPR, ORC]
Contract:
  Inputs: households, schools, local institutions
  Outputs: local education stability, safe corridors, load distribution
Core Pipelines:
  - RegenPipeline: local learning throughput + exam performance stability
  - MaintenancePipeline: consistent routines + low coordination friction
  - CoordinationPipeline: shared reality across parents/students/providers
Buffers:
  - Slack: spare tutoring capacity + time buffers
  - Redundancy: multiple institutions/providers
  - TTC: time-to-grade-collapse / time-to-family-burnout
Installed Modules:
  - FenceOS: yes
  - ERCO: yes
  - ChronoHelmAI: optional (recommended)
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS]
SensorPacks:
  - SENSORPACK_SGP_BTM_Z2_EDU_HCCP_MIN_v1
Notes:
  - INTERACTOS usually not needed at Z2 unless external actor conflict matters.

NodeID: INST:SGP:SGP:BTM:EDUKATE
Type: INSTITUTION
ZoomZ: Z1
PhaseP: P2→approaching P3 (confidence: medium)   # based on your internal status lock
LaneSet: [EDU]
OwnerRoles: [OPR, ORC, ARC]
Contract:
  Inputs: student signals, parent constraints, curriculum demands
  Outputs: capability regeneration, exam stability, repair protocols, AVOO training
Core Pipelines:
  - RegenPipeline: EducationOS repair loops (diagnose→train→retest)
  - MaintenancePipeline: tutor SOP, content update cadence, quality control
  - CoordinationPipeline: shared reality with parents/students; expectation control
Buffers:
  - Slack: tutor capacity buffer + schedule buffer
  - Redundancy: multi-tutor coverage + material redundancy
  - TTC: time-to-grade-collapse; time-to-burnout; time-to-trust-loss
Installed Modules:
  - FenceOS: yes
  - ERCO: yes
  - ChronoHelmAI: yes
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS]
SensorPacks:
  - SENSORPACK_EDUKATE_Z1_HCCP_MIN_v1
Notes:
  - This node is the “Ground Zero” execution platform for AVOO Academy (optional module below).

NodeID: ROLESET:AVOO
Type: ROLESET
ZoomZ: Z1
PhaseP: P3 (target; enforce via choice-budget control)
LaneSet: [EDU, GOV, ANY]
OwnerRoles: [ARC, VIS, ORC, OPR]
Contract:
  Inputs: problems under load
  Outputs: corridors (ARC), direction (VIS), truth/thresholds (ORC), stable execution (OPR)
Installed Modules:
  - ChoiceBudgetGuard (required)
  - FenceOS coupling (required)
Sensors:
  - RHO_CHOICE = choice_injection / capacity
  - SHEAR_PROXY (phase shear estimate)
Thresholds:
  - If RHO_CHOICE > θ_rho at Operator layer → reduce options; freeze changes.

NodeID: IND:ANON:0001
Type: IND
ZoomZ: Z0
PhaseP: unknown (measured)
LaneSet: [EDU]
OwnerRoles: [OPR/ORC]
Contract:
  Inputs: curriculum load + home constraints
  Outputs: performance under time + transfer stability
Sensors:
  - skill_leaks, timed_output_stability, fatigue, trust, attendance
Notes:
  - Keep anonymised; link by cohort tags only.

EdgeID: EDGE_SGP_HAS_CITY_01
FromNode: COUNTRY:SGP
ToNode: CITY:SGP:SGP
EdgeType: HAS_CHILD
Weight: 1.0
Latency: n/a
Contract:
  Flow: authority + funding + rules
  Failure: city execution decouples
  Repair: ACTOS + REALITYOS alignment
EdgeID: EDGE_CITY_HAS_DISTRICT_01
FromNode: CITY:SGP:SGP
ToNode: DISTRICT:SGP:SGP:BTM
EdgeType: HAS_CHILD
Weight: 0.8
Latency: weekly
Contract:
  Flow: standards + support + monitoring
  Failure: uneven phase drift across districts
  Repair: OBSOS coverage + local ERCO
EdgeID: EDGE_BTM_HAS_INST_01
FromNode: DISTRICT:SGP:SGP:BTM
ToNode: INST:SGP:SGP:BTM:EDUKATE
EdgeType: HAS_CHILD
Weight: 0.7
Latency: daily
Contract:
  Flow: student demand + local trust
  Failure: district loses regen throughput
  Repair: CAPGRAPHOS bottlenecks + REALITYOS trust repair
EdgeID: EDGE_EDUKATE_SERVES_IND_01
FromNode: INST:SGP:SGP:BTM:EDUKATE
ToNode: IND:ANON:*
EdgeType: SERVES
Weight: 0.9
Latency: session-based
Contract:
  Flow: instruction + repair
  Failure: P2→P1 student drift under load
  Repair: ERCO repair plan + retests
EdgeID: EDGE_EDUKATE_RUNS_AVOO_01
FromNode: INST:SGP:SGP:BTM:EDUKATE
ToNode: ROLESET:AVOO
EdgeType: RUNS
Weight: 0.6
Latency: weekly
Contract:
  Flow: training corridors + SOP lock
  Failure: operator overload / choice shear
  Repair: ChoiceBudgetGuard + ChronoHelm windows

SensorPackID: SENSORPACK_EDUKATE_Z1_HCCP_MIN_v1
AppliesToNode: INST:SGP:SGP:BTM:EDUKATE
UpdateCadence: weekly + event-driven
Sensors:
OBSOS:
  - OBS_COVERAGE
  - SIGNAL_LATENCY
  - DECEPTION_INDEX
  - SURPRISE_RATE
REALITYOS:
  - SHARED_REALITY_GAP
  - TRUST_DECAY_RATE
  - CONTRADICTION_DENSITY
  - NIT
ACTOS:
  - T_ENFORCE
  - EVASION_RATE
  - LEGITIMACY_DAMAGE_RATE
INCOS+CAPOS:
  - CAPTURE_INDEX
  - GOODHART_PRESSURE
  - RENT_SEEK_RATE
CAPGRAPHOS:
  - BOTTLENECK_CRITICALITY
  - SPOF_COUNT
  - TRAINING_THROUGHPUT
EXLEDGEROS:
  - MAINTENANCE_BACKLOG
  - DEFERRED_DAMAGE_RATE
  - TRUE_NET_REGEN
TOPOOS:
  - CHOKEPOINT_INDEX
  - ROUTE_REDUNDANCY
  - CORRIDOR_FRAGILITY

ThetaID: THETA_OBSOS_COV_01
Condition: OBS_COVERAGE < θ_cov
PhaseRisk: P2→P1
FenceTrigger:
  Actuation: PROBE (increase coverage) + FREEZE (stop changes)
  OwnerRole: ORC/OPR
  RetestCadence: 7 days
ExitCondition: OBS_COVERAGE ≥ θ_cov for 2 cycles
ThetaID: THETA_REALITY_NIT_01
Condition: NIT_STATUS = crossed
PhaseRisk: P1→P0 (coordination fracture)
FenceTrigger:
  Actuation: LOCALIZE + CORRIDOR_REPAIR
  OwnerRole: ORC
  RetestCadence: 14 days
ExitCondition: SHARED_REALITY_GAP inside band for 3 cycles
ThetaID: THETA_ACTOS_LAT_01
Condition: T_ENFORCE > θ_time AND EVASION_RATE rising
PhaseRisk: P2→P1
FenceTrigger:
  Actuation: REDESIGN (shift from enforcement to incentives/SOP)
  OwnerRole: OPR/ARC
  RetestCadence: 7 days
ExitCondition: T_ENFORCE ≤ θ_time AND EVASION_RATE stable/decreasing
ThetaID: THETA_CAPOS_GOODHART_01
Condition: GOODHART_PRESSURE > θ_gh
PhaseRisk: Hidden regen loss
FenceTrigger:
  Actuation: AUDIT + SENSOR_SWITCH (multi-metric + random checks)
  OwnerRole: ORC
  RetestCadence: 30 days
ExitCondition: gaming indicators fall for 2 cycles

RUN_ID: RUN_EDUKATE_HCCP_001
PlaceChain: CHAIN_SGP_SGP_BTM_EDUKATE_v1
Inputs:
  - SENSORPACK_EDUKATE_Z1_HCCP_MIN_v1 values + trends
  - PhaseP estimate: P2
Steps:
1) Phase×Zoom diagnosis (Z1)
2) Top 5 risks (sensor→threshold→failure trace)
3) Fence triggers (immediate stop-loss)
4) Repair plan:
   - Truncation actions
   - Stitching actions
   - Localize/reduce coupling
   - Redesign incentives/SOP
5) ChronoHelmAI windows:
   - FREEZE: protect Operator stability
   - SANDBOX: Architect exploration
   - DEPLOY: rollout + monitoring
6) Retest + exit conditions
Outputs:
  - Updated PhaseP estimate + confidence
  - Next run date

ModuleID: CIVOS_MODULE_AVOO_ACADEMY_01
AppliesToNode: INST:SGP:SGP:BTM:EDUKATE
Contract:
- Train ARC→VIS→ORC→OPR corridors without injecting excess choice into Operator layer.
Sensors:
- RHO_CHOICE (Operator)
- SHEAR_PROXY
Threshold:
- If RHO_CHOICE > θ_rho → FREEZE curriculum changes; revert to SOP set; reopen sandbox only.

PROMPT_PLACE_DEEPDIVE_RUNNER_v1:
Run CivOS Place Deep Dive (Z3→Z0) with HCCP v1.0.
Input:
- PlaceChain
- NodeRecords + EdgeRecords
- SENSORPACK values + trend
- Current Phase estimates
Output (strict):
1) Phase×Zoom diagnosis (Z3/Z2/Z1/Z0)
2) Top 5 risks per level (sensor→threshold→failure trace)
3) FenceOS triggers (immediate)
4) ERCO repair plan (truncate/stitch/localize/redesign)
5) ChronoHelmAI schedule windows
6) Retest plan + exit conditions

TITLE: COUNTRY:SGP CivOS Directory (Z5) — v1.0
Slug: /civos-place-country-sgp-z5-v1-0/
Runtime: CivOS_Runtime v1.x + HCCP v1.0
NodeID: COUNTRY:SGP
ZoomZ: Z5
LaneSet: [GOV, EDU, FIN, HLTH]

PLACE_NODE_LOCK:
NodeID: COUNTRY:SGP
ZoomZ: Z5
Meaning: National coordination + regeneration envelope over time
DoNotRename: true
VersionForwardOnly: true
InstalledPacks:
  - CivOS_AddOn_HCCP_v1.0
  - FenceOS (required)
  - ERCO (required)
  - ChronoHelmAI (recommended)

NodeID: COUNTRY:SGP
Type: COUNTRY
ZoomZ: Z5
PhaseP: P2 (confidence: medium)
OwnerRoles: [ORC, OPR, ARC]
Contract:
  Inputs: global shocks, trade flows, migration, information flows
  Outputs: national rule execution, funding, national pipelines stability
Core Pipelines:
  - RegenPipeline: EducationOS (capability regeneration across generations)
  - MaintenancePipeline: institutional continuity + staffing continuity
  - CoordinationPipeline: shared reality + enforcement timing + incentive alignment
Buffers:
  - Slack: policy + fiscal + time buffers
  - Redundancy: multi-route supply, multi-provider pipelines
  - TTC: national time-to-core failure (must be monitored)
Installed Modules (HCCP):
  - OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS, INTERACTOS
SensorPack:
  - SENSORPACK_SGP_Z5_HCCP_MIN_v1
ThresholdPack:
  - THETAPACK_SGP_Z5_HCCP_CORE_v1

LANE_DIR_Z5_SGP_v1:
- LANE:GOV:SGP (Z5)  → rule execution, legitimacy, enforcement capacity
- LANE:EDU:SGP (Z5)  → capability regeneration throughput
- LANE:FIN:SGP (Z5)  → allocation + incentives + capture risk
- LANE:HLTH:SGP (Z5) → health capacity + shock absorption

ORG_LIST_FORMAT_v1:
# Z6 (Top-level org registry entries)
Z6_ORG_ENTRY:
  OrgID: ORG:<ISO3>:<LANE>:<ORGCODE>
  Name: <string>
  ZoomZ: Z6
  Lane: <LANE>
  RoleOwner: [OPR/ORC/ARC/VIS]
  Criticality: (low/med/high)
  Notes: <optional>
# Z1 (Execution institutions inside districts/cities)
Z1_INST_ENTRY:
  InstID: INST:<ISO3>:<CITY>:<DISTRICT>:<INSTCODE>
  Name: <string>
  ZoomZ: Z1
  Lane: <LANE>
  PrimaryContract: <inputs→outputs>
  SensorPack: <id>

SensorPackID: SENSORPACK_SGP_Z5_HCCP_MIN_v1
Cadence: weekly + event-driven
Sensors:
  OBSOS: OBS_COVERAGE, SIGNAL_LATENCY, DECEPTION_INDEX, SURPRISE_RATE
  REALITYOS: SHARED_REALITY_GAP, TRUST_DECAY_RATE, CONTRADICTION_DENSITY, NIT
  ACTOS: T_ENFORCE, EVASION_RATE, LEGITIMACY_DAMAGE_RATE
  INCOS+CAPOS: CAPTURE_INDEX, GOODHART_PRESSURE, RENT_SEEK_RATE
  CAPGRAPHOS: BOTTLENECK_CRITICALITY, SPOF_COUNT, TRAINING_THROUGHPUT
  EXLEDGEROS: MAINTENANCE_BACKLOG, DEFERRED_DAMAGE_RATE, TRUE_NET_REGEN
  TOPOOS: CHOKEPOINT_INDEX, ROUTE_REDUNDANCY, CORRIDOR_FRAGILITY
  INTERACTOS: MISPERCEPTION_PROB, ESCALATION_LADDER_POSITION

PROMPT_COUNTRY_SGP_RUNNER_v1:
Run CivOS COUNTRY:SGP with HCCP v1.0.
Return: Phase×Zoom diagnosis + top 5 risks (sensor→threshold→failure trace) +
Fence triggers + ERCO plan + ChronoHelmAI windows + retest + exit conditions.

TITLE: CITY:SGP:SGP CivOS Directory (Z3) — v1.0
Slug: /civos-place-city-sgp-sgp-z3-v1-0/
Runtime: CivOS_Runtime v1.x + HCCP v1.0
NodeID: CITY:SGP:SGP
ZoomZ: Z3
LaneSet: [GOV, EDU, FIN, HLTH]

NodeID: CITY:SGP:SGP
Type: CITY
ZoomZ: Z3
PhaseP: P2 (confidence: medium)
OwnerRoles: [OPR, ORC, ARC]
Installed Modules:
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS, INTERACTOS]
  - FenceOS: yes
  - ERCO: yes
  - ChronoHelmAI: yes
SensorPack: SENSORPACK_SGP_CITY_Z3_HCCP_MIN_v1
ThresholdPack: THETAPACK_SGP_CITY_Z3_HCCP_CORE_v1
Children:
  - DISTRICT:* (Z2)

EDGES:
- EDGE_SGP_HAS_CITY_01: COUNTRY:SGP → CITY:SGP:SGP (HAS_CHILD)
- EDGE_CITY_HAS_DISTRICT_*: CITY:SGP:SGP → DISTRICT:* (HAS_CHILD)

LANE_DIR_Z3_CITY_SGP_v1:
- EDU: schools + tuition ecosystem + teacher pipeline + exam stability
- GOV: actuation latency + compliance + legitimacy control
- FIN: allocation + incentive alignment + capture control
- HLTH: surge capacity + shock absorption

Z1_CITY_INST_REGISTRY_FORMAT_v1:
InstID: INST:SGP:SGP:<DISTRICT>:<INSTCODE>
Lane: <EDU/GOV/FIN/HLTH>
Criticality: (low/med/high)
SensorPack: <id>

PROMPT_CITY_SGP_RUNNER_v1:
Run CITY:SGP:SGP (Z3) focusing on TOPOOS + EXLEDGEROS + CAPGRAPHOS early warnings.
Output: chokepoints, backlogs, bottlenecks, plus Fence/ERCO actions.

TITLE: DISTRICT:SGP:SGP:BTM CivOS Directory (Z2) — v1.0
Slug: /civos-place-district-sgp-sgp-btm-z2-v1-0/
Runtime: CivOS_Runtime v1.x + HCCP v1.0
NodeID: DISTRICT:SGP:SGP:BTM
ZoomZ: Z2
LaneSet: [EDU, GOV]

NodeID: DISTRICT:SGP:SGP:BTM
Type: DISTRICT
ZoomZ: Z2
PhaseP: P2→P3 (confidence: low-to-medium)
OwnerRoles: [OPR, ORC]
Installed Modules:
  - HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS]
  - FenceOS: yes
  - ERCO: yes
  - ChronoHelmAI: optional (recommended)
SensorPack: SENSORPACK_SGP_BTM_Z2_EDU_HCCP_MIN_v1
ThresholdPack: THETAPACK_SGP_BTM_Z2_EDU_CORE_v1
Children:
  - INST:* (Z1)

Z1_INST_REGISTRY_SGP_BTM_v1:
- INST:SGP:SGP:BTM:EDUKATE   (EDU)  SensorPack: SENSORPACK_EDUKATE_Z1_HCCP_MIN_v1
- INST:SGP:SGP:BTM:<SCH001>  (EDU)  SensorPack: <id>
- INST:SGP:SGP:BTM:<SCH002>  (EDU)  SensorPack: <id>
- INST:SGP:SGP:BTM:<GOV001>  (GOV)  SensorPack: <id>
(Expand later; keep format stable.)

PROMPT_DISTRICT_BTM_RUNNER_v1:
Run DISTRICT:SGP:SGP:BTM focusing on:
- REALITYOS: trust decay + irreversibility status
- CAPGRAPHOS: bottlenecks affecting learning throughput
- ACTOS: response latency to incidents
Output: district repair plan + which institutions to reinforce first.

TITLE: INST:SGP:SGP:BTM:EDUKATE CivOS Directory (Z1) — v1.0
Slug: /civos-place-inst-sgp-sgp-btm-edukate-z1-v1-0/
Runtime: CivOS_Runtime v1.x + HCCP v1.0
NodeID: INST:SGP:SGP:BTM:EDUKATE
ZoomZ: Z1
LaneSet: [EDU]

INST_LOCK:
NodeID: INST:SGP:SGP:BTM:EDUKATE
ZoomZ: Z1
Lane: EDU
Contract: Diagnose→Repair→Retest (EducationOS) + HCCP sensorization
DoNotRename: true

NodeID: INST:SGP:SGP:BTM:EDUKATE
Type: INSTITUTION
ZoomZ: Z1
PhaseP: P2→approaching P3 (confidence: medium)
OwnerRoles: [OPR, ORC, ARC]
Core Pipelines:
- RegenPipeline: EducationOS closed-loop repair (diagnose→train→retest)
- MaintenancePipeline: tutor SOP, content upkeep, quality control
- CoordinationPipeline: shared reality with parents/students, expectation control
Installed:
- FenceOS: yes
- ERCO: yes
- ChronoHelmAI: yes
- HCCP: [OBSOS, REALITYOS, ACTOS, INCOS+CAPOS, CAPGRAPHOS, EXLEDGEROS, TOPOOS]
- Optional: AVOO_Academy module (corridors + choice-budget guard)
SensorPack: SENSORPACK_EDUKATE_Z1_HCCP_MIN_v1
ThresholdPack: THETAPACK_EDUKATE_Z1_HCCP_CORE_v1

EDGES:
- EDGE_BTM_HAS_INST_01: DISTRICT:SGP:SGP:BTM → INST:SGP:SGP:BTM:EDUKATE (HAS_CHILD)
- EDGE_EDUKATE_SERVES_IND_01: INST:...:EDUKATE → IND:ANON:* (SERVES)
- EDGE_EDUKATE_RUNS_AVOO_01: INST:...:EDUKATE → ROLESET:AVOO (RUNS)

ModuleID: CIVOS_MODULE_AVOO_ACADEMY_01
Contract:
- Train ARC→VIS→ORC→OPR corridors without injecting excess choice into OPR layer.
Sensors:
- RHO_CHOICE_OPR
- SHEAR_PROXY
Fence:
- If RHO_CHOICE_OPR > θ_rho → FREEZE changes, revert SOP set, reopen only SANDBOX.

Z0_IND_REGISTRY_FORMAT_v1:
- IND:ANON:<COHORT>:<SEQ>
  CohortTag: (P6_2026 / Sec2_2026 / etc.)
  SensorMini: timed_stability, skill_leaks, fatigue, trust
  RetestCadence: weekly/biweekly

PROMPT_EDUKATE_Z1_RUNNER_v1:
Run INST:SGP:SGP:BTM:EDUKATE with HCCP v1.0.
Output strictly:
1) Z1 Phase diagnosis
2) Top 5 risks (sensor→threshold→failure trace)
3) Fence triggers
4) ERCO plan (truncate/stitch/localize/redesign)
5) ChronoHelmAI windows (Freeze/Sandbox/Deploy)
6) Retest + exit conditions

LANE_DIRECTORY_PACK_v1:
LANE:EDU:
  - Purpose: regenerate capability throughput across generations
  - Critical modules: CAPGRAPHOS, REALITYOS, OBSOS
LANE:GOV:
  - Purpose: rule execution + legitimacy + actuation capacity
  - Critical modules: ACTOS, REALITYOS, OBSOS
LANE:FIN:
  - Purpose: allocation + incentives + capture control
  - Critical modules: INCOS+CAPOS, EXLEDGEROS
LANE:HLTH:
  - Purpose: shock absorption + capacity buffers
  - Critical modules: CAPGRAPHOS, TOPOOS, OBSOS

NORMALIZATION_LOCK_v1:
Sensor polarity:
- "GOOD when HIGH": OBS_COVERAGE, ROUTE_REDUNDANCY, TRUE_NET_REGEN (if used as surplus)
- "BAD when HIGH": SIGNAL_LATENCY, SURPRISE_RATE, DECEPTION_INDEX, TRUST_DECAY_RATE,
  CONTRADICTION_DENSITY, SHARED_REALITY_GAP, NIT_SCORE, T_ENFORCE, EVASION_RATE,
  LEGITIMACY_DAMAGE_RATE, CAPTURE_INDEX, GOODHART_PRESSURE, RENT_SEEK_RATE,
  BOTTLENECK_CRITICALITY, SPOF_COUNT, MAINTENANCE_BACKLOG, DEFERRED_DAMAGE_RATE,
  CHOKEPOINT_INDEX, CORRIDOR_FRAGILITY, MISPERCEPTION_PROB, ESCALATION_LADDER_POSITION,
  RHO_CHOICE_OPR
Normalize to [0,1] if not already:
- norm(x) = clamp((x - p10_baseline)/(p90_baseline - p10_baseline), 0, 1)
  where p10/p90 are from a baseline window (see protocol).
NIT representation:
- Use NIT_SCORE ∈ [0,1] where 1 = “irreversibility crossed”.
  (If you currently track NIT_STATUS, map: approaching=0.7, crossed=1.0, safe=0.0)

THETAPACK_Z1_HCCP_CORE_v1:
# OBSOS
θ_cov_green_min = 0.70
θ_cov_amber_min = 0.55
θ_cov_red_min   = 0.40
θ_latency_green_max = 0.30   # normalized latency
θ_latency_amber_max = 0.55
θ_latency_red_max   = 0.75
θ_surprise_green_max = 0.35
θ_surprise_amber_max = 0.55
θ_surprise_red_max   = 0.70
θ_deception_amber = 0.60
θ_deception_red   = 0.75
# REALITYOS
θ_trust_decay_amber = 0.55
θ_trust_decay_red   = 0.70
θ_reality_gap_amber = 0.55
θ_reality_gap_red   = 0.70
θ_contradiction_amber = 0.55
θ_contradiction_red   = 0.70
θ_nit_approach = 0.70
θ_nit_crossed  = 0.90
# ACTOS
θ_t_enforce_amber = 0.55
θ_t_enforce_red   = 0.70
θ_evasion_amber = 0.55
θ_evasion_red   = 0.70
θ_legit_damage_amber = 0.55
θ_legit_damage_red   = 0.70
# INCOS+CAPOS
θ_capture_amber = 0.55
θ_capture_red   = 0.70
θ_goodhart_amber = 0.55
θ_goodhart_red   = 0.70
# CAPGRAPHOS
θ_bottleneck_amber = 0.55
θ_bottleneck_red   = 0.70
θ_spof_amber = 0.55
θ_spof_red   = 0.70
# EXLEDGEROS
θ_backlog_amber = 0.55
θ_backlog_red   = 0.70
θ_deferred_damage_amber = 0.55
θ_deferred_damage_red   = 0.70
# TOPOOS
θ_chokepoint_amber = 0.55
θ_chokepoint_red   = 0.70
θ_corridor_fragility_amber = 0.55
θ_corridor_fragility_red   = 0.70
# AVOO Choice Budget (if installed)
θ_rho_choice_opr_amber = 0.55
θ_rho_choice_opr_red   = 0.70

THETAPACK_Z2_HCCP_CORE_v1:
# OBSOS (district needs more coverage than you think)
θ_cov_green_min = 0.75
θ_cov_amber_min = 0.60
θ_cov_red_min   = 0.45
θ_surprise_green_max = 0.30
θ_surprise_amber_max = 0.50
θ_surprise_red_max   = 0.65
θ_deception_amber = 0.55
θ_deception_red   = 0.70
# REALITYOS (trust and shared reality matter more at Z2)
θ_trust_decay_amber = 0.50
θ_trust_decay_red   = 0.65
θ_reality_gap_amber = 0.50
θ_reality_gap_red   = 0.65
θ_nit_approach = 0.65
θ_nit_crossed  = 0.85
# ACTOS (latency is costly because issues spread locally)
θ_t_enforce_amber = 0.50
θ_t_enforce_red   = 0.65
θ_legit_damage_amber = 0.50
θ_legit_damage_red   = 0.65
# INCOS+CAPOS (capture shows up as “coordination rot”)
θ_capture_amber = 0.50
θ_capture_red   = 0.65
θ_goodhart_amber = 0.50
θ_goodhart_red   = 0.65
# CAPGRAPHOS / EXLEDGEROS / TOPOOS
θ_bottleneck_amber = 0.50
θ_bottleneck_red   = 0.65
θ_deferred_damage_amber = 0.50
θ_deferred_damage_red   = 0.65
θ_chokepoint_amber = 0.50
θ_chokepoint_red   = 0.65
# AVOO Choice Budget
θ_rho_choice_opr_amber = 0.50
θ_rho_choice_opr_red   = 0.65

THETAPACK_Z3_HCCP_CORE_v1:
# OBSOS (city should be sensor-rich)
θ_cov_green_min = 0.80
θ_cov_amber_min = 0.65
θ_cov_red_min   = 0.50
θ_surprise_green_max = 0.25
θ_surprise_amber_max = 0.45
θ_surprise_red_max   = 0.60
θ_deception_amber = 0.50
θ_deception_red   = 0.65
# REALITYOS (fragmentation is expensive but slower than Z2)
θ_trust_decay_amber = 0.55
θ_trust_decay_red   = 0.70
θ_reality_gap_amber = 0.55
θ_reality_gap_red   = 0.70
θ_nit_approach = 0.70
θ_nit_crossed  = 0.90
# ACTOS (actuation must beat TTC)
θ_t_enforce_amber = 0.55
θ_t_enforce_red   = 0.70
θ_legit_damage_amber = 0.55
θ_legit_damage_red   = 0.70
# INCOS+CAPOS (metric gaming becomes systemic)
θ_capture_amber = 0.55
θ_capture_red   = 0.70
θ_goodhart_amber = 0.55
θ_goodhart_red   = 0.70
# CAPGRAPHOS (bottlenecks are city-killers)
θ_bottleneck_amber = 0.45
θ_bottleneck_red   = 0.60
# EXLEDGEROS (backlog + deferred damage must be watched tightly)
θ_backlog_amber = 0.45
θ_backlog_red   = 0.60
θ_deferred_damage_amber = 0.45
θ_deferred_damage_red   = 0.60
# TOPOOS (chokepoints should trigger early)
θ_chokepoint_amber = 0.45
θ_chokepoint_red   = 0.60
θ_corridor_fragility_amber = 0.45
θ_corridor_fragility_red   = 0.60
# INTERACTOS (if applicable at city level)
θ_misperception_amber = 0.55
θ_misperception_red   = 0.70

THETAPACK_Z5_HCCP_CORE_v1:
# OBSOS (national truth must be strong)
θ_cov_green_min = 0.85
θ_cov_amber_min = 0.70
θ_cov_red_min   = 0.55
θ_surprise_green_max = 0.25
θ_surprise_amber_max = 0.40
θ_surprise_red_max   = 0.55
θ_deception_amber = 0.50
θ_deception_red   = 0.65
# REALITYOS (irreversibility is catastrophic; trigger earlier)
θ_trust_decay_amber = 0.50
θ_trust_decay_red   = 0.65
θ_reality_gap_amber = 0.50
θ_reality_gap_red   = 0.65
θ_nit_approach = 0.60
θ_nit_crossed  = 0.80
# ACTOS (overuse damages legitimacy at scale)
θ_legit_damage_amber = 0.50
θ_legit_damage_red   = 0.65
θ_t_enforce_amber = 0.60
θ_t_enforce_red   = 0.75
# INCOS+CAPOS (capture kills true regen)
θ_capture_amber = 0.50
θ_capture_red   = 0.65
θ_goodhart_amber = 0.50
θ_goodhart_red   = 0.65
# CAPGRAPHOS (SPOFs and bottlenecks must be addressed early)
θ_bottleneck_amber = 0.45
θ_bottleneck_red   = 0.60
θ_spof_amber = 0.45
θ_spof_red   = 0.60
# EXLEDGEROS (national collapse often “debt service spikes”)
θ_backlog_amber = 0.45
θ_backlog_red   = 0.60
θ_deferred_damage_amber = 0.40
θ_deferred_damage_red   = 0.55
# TOPOOS (chokepoints are strategic vulnerabilities)
θ_chokepoint_amber = 0.40
θ_chokepoint_red   = 0.55
# INTERACTOS (misperception + escalation must trigger early)
θ_misperception_amber = 0.45
θ_misperception_red   = 0.60
θ_escalation_ladder_amber = 0.55
θ_escalation_ladder_red   = 0.70

THETA_TO_FENCE_MAP_v1:
If OBS_COVERAGE < θ_cov_red:
  FENCE: FREEZE + PROBE (increase coverage; cut latency)
If SURPRISE_RATE > θ_surprise_red OR DECEPTION_INDEX > θ_deception_red:
  FENCE: AUDIT + COUNTER_SIGNAL + RED_TEAM
If NIT_SCORE ≥ θ_nit_crossed:
  FENCE: LOCALIZE + CORRIDOR_REPAIR (contain spread, rebuild shared reality)
If LEGITIMACY_DAMAGE_RATE > θ_legit_damage_red:
  FENCE: STOP_LOSS (reduce enforcement intensity, increase transparency)
If CAPTURE_INDEX > θ_capture_red OR GOODHART_PRESSURE > θ_goodhart_red:
  FENCE: FREEZE allocations + ROTATE roles + AUDIT binds + SENSOR_SWITCH
If BOTTLENECK_CRITICALITY > θ_bottleneck_red OR SPOF_COUNT > θ_spof_red:
  FENCE: REDUNDANCY_BUILD + UPSTREAM_REPAIR (CAPGRAPHOS)
If DEFERRED_DAMAGE_RATE > θ_deferred_damage_red OR BACKLOG > θ_backlog_red:
  FENCE: TRUNCATE growth + PRIORITIZE repair (EXLEDGEROS)
If CHOKEPOINT_INDEX > θ_chokepoint_red OR CORRIDOR_FRAGILITY > θ_corridor_fragility_red:
  FENCE: BYPASS + LOCAL BUFFERS + COUPLING_REDUCTION (TOPOOS)
If MISPERCEPTION_PROB > θ_misperception_red OR ESCALATION_LADDER_POSITION > θ_escalation_ladder_red:
  FENCE: VERIFICATION_UP + COOLDOWN_WINDOW (ChronoHelmAI enforced)

CALIBRATION_PROTOCOL_THETA_v1:
Goal: turn defaults into local truth without heavy data work.
Step 1 — Baseline window:
- Collect 4 weeks (or 8 cycles) of sensor values at the node.
Step 2 — Compute p10 / p90:
- For each sensor s: p10_s, p90_s.
Step 3 — Normalize:
- norm(s) = clamp((s - p10_s)/(p90_s - p10_s), 0, 1)
Step 4 — Adopt Z-level ThetaPack defaults:
- Use the Z1/Z2/Z3/Z5 numbers above as your band boundaries.
Step 5 — Tighten only if you get false negatives:
- If failures happened while sensors stayed “green”, lower amber/red thresholds by 0.05–0.10.
Step 6 — Loosen only if you get constant false alarms:
- If everything stays “amber” with no real incidents, raise amber/red by 0.05 (never more than 0.10 per revision).
Version forward:
- THETAPACK_*_v1 → v1.1 → v1.2 (never overwrite history).

THETAPACK_ID: THETAPACK_EDUKATE_Z1_HCCP_CORE_v1
AppliesToNode: INST:SGP:SGP:BTM:EDUKATE
ZoomZ: Z1
Pack: HCCP v1.0
# OBSOS
θ_cov_green_min = 0.70
θ_cov_amber_min = 0.55
θ_cov_red_min   = 0.40
θ_latency_green_max = 0.30
θ_latency_amber_max = 0.55
θ_latency_red_max   = 0.75
θ_surprise_green_max = 0.35
θ_surprise_amber_max = 0.55
θ_surprise_red_max   = 0.70
θ_deception_amber = 0.60
θ_deception_red   = 0.75
# REALITYOS
θ_trust_decay_amber = 0.55
θ_trust_decay_red   = 0.70
θ_reality_gap_amber = 0.55
θ_reality_gap_red   = 0.70
θ_contradiction_amber = 0.55
θ_contradiction_red   = 0.70
θ_nit_approach = 0.70
θ_nit_crossed  = 0.90
# ACTOS
θ_t_enforce_amber = 0.55
θ_t_enforce_red   = 0.70
θ_evasion_amber = 0.55
θ_evasion_red   = 0.70
θ_legit_damage_amber = 0.55
θ_legit_damage_red   = 0.70
# INCOS+CAPOS
θ_capture_amber = 0.55
θ_capture_red   = 0.70
θ_goodhart_amber = 0.55
θ_goodhart_red   = 0.70
# CAPGRAPHOS
θ_bottleneck_amber = 0.55
θ_bottleneck_red   = 0.70
θ_spof_amber = 0.55
θ_spof_red   = 0.70
# EXLEDGEROS
θ_backlog_amber = 0.55
θ_backlog_red   = 0.70
θ_deferred_damage_amber = 0.55
θ_deferred_damage_red   = 0.70
# TOPOOS
θ_chokepoint_amber = 0.55
θ_chokepoint_red   = 0.70
θ_corridor_fragility_amber = 0.55
θ_corridor_fragility_red   = 0.70
# AVOO Choice Budget (if installed at Z1)
θ_rho_choice_opr_amber = 0.55
θ_rho_choice_opr_red   = 0.70

THETAPACK_ID: THETAPACK_SGP_BTM_Z2_EDU_CORE_v1
AppliesToNode: DISTRICT:SGP:SGP:BTM
ZoomZ: Z2
Lane: EDU
Pack: HCCP v1.0
# OBSOS
θ_cov_green_min = 0.75
θ_cov_amber_min = 0.60
θ_cov_red_min   = 0.45
θ_surprise_green_max = 0.30
θ_surprise_amber_max = 0.50
θ_surprise_red_max   = 0.65
θ_deception_amber = 0.55
θ_deception_red   = 0.70
# REALITYOS
θ_trust_decay_amber = 0.50
θ_trust_decay_red   = 0.65
θ_reality_gap_amber = 0.50
θ_reality_gap_red   = 0.65
θ_nit_approach = 0.65
θ_nit_crossed  = 0.85
# ACTOS
θ_t_enforce_amber = 0.50
θ_t_enforce_red   = 0.65
θ_legit_damage_amber = 0.50
θ_legit_damage_red   = 0.65
# INCOS+CAPOS
θ_capture_amber = 0.50
θ_capture_red   = 0.65
θ_goodhart_amber = 0.50
θ_goodhart_red   = 0.65
# CAPGRAPHOS
θ_bottleneck_amber = 0.50
θ_bottleneck_red   = 0.65
# EXLEDGEROS
θ_deferred_damage_amber = 0.50
θ_deferred_damage_red   = 0.65
# TOPOOS
θ_chokepoint_amber = 0.50
θ_chokepoint_red   = 0.65
# AVOO Choice Budget (district-level operator shear)
θ_rho_choice_opr_amber = 0.50
θ_rho_choice_opr_red   = 0.65

THETAPACK_ID: THETAPACK_SGP_CITY_Z3_HCCP_CORE_v1
AppliesToNode: CITY:SGP:SGP
ZoomZ: Z3
Pack: HCCP v1.0
# OBSOS
θ_cov_green_min = 0.80
θ_cov_amber_min = 0.65
θ_cov_red_min   = 0.50
θ_surprise_green_max = 0.25
θ_surprise_amber_max = 0.45
θ_surprise_red_max   = 0.60
θ_deception_amber = 0.50
θ_deception_red   = 0.65
# REALITYOS
θ_trust_decay_amber = 0.55
θ_trust_decay_red   = 0.70
θ_reality_gap_amber = 0.55
θ_reality_gap_red   = 0.70
θ_nit_approach = 0.70
θ_nit_crossed  = 0.90
# ACTOS
θ_t_enforce_amber = 0.55
θ_t_enforce_red   = 0.70
θ_legit_damage_amber = 0.55
θ_legit_damage_red   = 0.70
# INCOS+CAPOS
θ_capture_amber = 0.55
θ_capture_red   = 0.70
θ_goodhart_amber = 0.55
θ_goodhart_red   = 0.70
# CAPGRAPHOS (trigger earlier at city scale)
θ_bottleneck_amber = 0.45
θ_bottleneck_red   = 0.60
# EXLEDGEROS (trigger earlier)
θ_backlog_amber = 0.45
θ_backlog_red   = 0.60
θ_deferred_damage_amber = 0.45
θ_deferred_damage_red   = 0.60
# TOPOOS (trigger earlier)
θ_chokepoint_amber = 0.45
θ_chokepoint_red   = 0.60
θ_corridor_fragility_amber = 0.45
θ_corridor_fragility_red   = 0.60
# INTERACTOS (if applicable)
θ_misperception_amber = 0.55
θ_misperception_red   = 0.70

THETAPACK_ID: THETAPACK_SGP_Z5_HCCP_CORE_v1
AppliesToNode: COUNTRY:SGP
ZoomZ: Z5
Pack: HCCP v1.0
# OBSOS
θ_cov_green_min = 0.85
θ_cov_amber_min = 0.70
θ_cov_red_min   = 0.55
θ_surprise_green_max = 0.25
θ_surprise_amber_max = 0.40
θ_surprise_red_max   = 0.55
θ_deception_amber = 0.50
θ_deception_red   = 0.65
# REALITYOS (irreversibility triggers earlier)
θ_trust_decay_amber = 0.50
θ_trust_decay_red   = 0.65
θ_reality_gap_amber = 0.50
θ_reality_gap_red   = 0.65
θ_nit_approach = 0.60
θ_nit_crossed  = 0.80
# ACTOS (legitimacy damage is costly at scale)
θ_legit_damage_amber = 0.50
θ_legit_damage_red   = 0.65
θ_t_enforce_amber = 0.60
θ_t_enforce_red   = 0.75
# INCOS+CAPOS
θ_capture_amber = 0.50
θ_capture_red   = 0.65
θ_goodhart_amber = 0.50
θ_goodhart_red   = 0.65
# CAPGRAPHOS
θ_bottleneck_amber = 0.45
θ_bottleneck_red   = 0.60
θ_spof_amber = 0.45
θ_spof_red   = 0.60
# EXLEDGEROS (deferred damage triggers earliest)
θ_backlog_amber = 0.45
θ_backlog_red   = 0.60
θ_deferred_damage_amber = 0.40
θ_deferred_damage_red   = 0.55
# TOPOOS (strategic chokepoints)
θ_chokepoint_amber = 0.40
θ_chokepoint_red   = 0.55
# INTERACTOS
θ_misperception_amber = 0.45
θ_misperception_red   = 0.60
θ_escalation_ladder_amber = 0.55
θ_escalation_ladder_red   = 0.70

FILE_ID: CIVOS_FILE_THETA_TO_FENCE_MAP_v1
Title: Theta→Fence Mapping (Canonical)
Slug: /civos-runtime-theta-to-fence-map-v1/
Applies: All nodes using HCCP v1.0 + FenceOS
MAP_RULES:
- AMBER = ERCO repair corridor (stitching/truncation plan, no hard stop unless compounding)
- RED   = FenceOS stop-loss actuation (freeze/localize/audit/redesign)
- If 2+ AMBER conditions persist for 2 cycles → treat as RED (compound drift rule)
------------------------------------------------------------
OBSOS (Observability / Hidden State)
------------------------------------------------------------
IF OBS_COVERAGE < θ_cov_red:
  FENCE: FREEZE + PROBE
  - FREEZE: stop new changes that increase uncertainty
  - PROBE: increase coverage, reduce latency, diversify sources
  RETEST: next cycle (≤ 7 days for Z1/Z2, ≤ 14 days for Z3/Z5)
IF SURPRISE_RATE > θ_surprise_red:
  FENCE: FREEZE + PROBE + LOCALIZE
  - LOCALIZE: reduce coupling until model re-locks truth
IF DECEPTION_INDEX > θ_deception_red:
  FENCE: AUDIT + COUNTER_SIGNAL + RED_TEAM
  - AUDIT: independent verification channel
  - COUNTER_SIGNAL: anti-noise comms protocol
  - RED_TEAM: adversarial testing of assumptions
------------------------------------------------------------
REALITYOS (Shared Reality / Legitimacy / Irreversibility)
------------------------------------------------------------
IF NIT_SCORE ≥ θ_nit_crossed:
  FENCE: CONTAIN + LOCALIZE + CORRIDOR_REPAIR
  - CONTAIN: stop spread of contradictory directives
  - LOCALIZE: decentralize decisions to reduce shear
  - CORRIDOR_REPAIR: rebuild shared reality via consistent definitions + proof loops
  RETEST: 14 days (or 2 cycles) with SHARED_REALITY_GAP, TRUST_DECAY_RATE
IF TRUST_DECAY_RATE > θ_trust_decay_red OR SHARED_REALITY_GAP > θ_reality_gap_red:
  FENCE: FREEZE POLICY CHANGES + SIMPLIFY SOP (AVOO coupling)
  - Reduce Operator choice injection (ChoiceBudgetGuard)
------------------------------------------------------------
ACTOS (Actuation / Enforcement Capacity)
------------------------------------------------------------
IF LEGITIMACY_DAMAGE_RATE > θ_legit_damage_red:
  FENCE: STOP_LOSS (de-escalate)
  - Reduce enforcement intensity
  - Increase transparency + procedural justice
  - Shift to Incentive redesign (INCOS+CAPOS)
  RETEST: legitimacy damage trend + compliance proxy
IF T_ENFORCE > θ_t_enforce_red AND EVASION_RATE rising:
  FENCE: REDESIGN (don’t brute-force)
  - Mechanism redesign (INCOS+CAPOS)
  - Reduce ruleset complexity
  - Increase automation where safe
  RETEST: T_ENFORCE, EVASION_RATE
------------------------------------------------------------
INCOS+CAPOS (Incentives / Capture / Goodhart)
------------------------------------------------------------
IF CAPTURE_INDEX > θ_capture_red:
  FENCE: FREEZE ALLOCATIONS + ROTATE ROLES + AUDIT BINDS
  - Freeze: pause sensitive transfers/procurements
  - Rotate: break repeated-game capture
  - Audit: trace benefit flows
  RETEST: CAPTURE_INDEX, RENT_SEEK_RATE
IF GOODHART_PRESSURE > θ_goodhart_red:
  FENCE: SENSOR_SWITCH + RANDOMIZED AUDITS
  - Replace single target metric with multi-metric basket
  - Random checks to reduce gaming payoff
  RETEST: gaming indicators + outcome stability
------------------------------------------------------------
CAPGRAPHOS (Capability Bottlenecks / SPOFs)
------------------------------------------------------------
IF BOTTLENECK_CRITICALITY > θ_bottleneck_red OR SPOF_COUNT > θ_spof_red:
  FENCE: REDUNDANCY_BUILD + UPSTREAM_REPAIR
  - Duplicate pipelines for SPOFs
  - Training throughput boost (EducationOS coupling)
  RETEST: bottleneck measure + throughput
------------------------------------------------------------
EXLEDGEROS (Externalities / Deferred Damage)
------------------------------------------------------------
IF DEFERRED_DAMAGE_RATE > θ_deferred_damage_red OR MAINTENANCE_BACKLOG > θ_backlog_red:
  FENCE: TRUNCATE GROWTH + PRIORITIZE REPAIR
  - Cut optional expansion
  - Protect repair budget + maintenance time
  RETEST: backlog slope; deferred damage slope
IF TRUE_NET_REGEN < Ḋ (operational):
  FENCE: ENTER RECOVERY CORRIDOR (P-upgrade plan)
  - Truncation + stitching sequence required
------------------------------------------------------------
TOPOOS (Topology / Chokepoints / Corridors)
------------------------------------------------------------
IF CHOKEPOINT_INDEX > θ_chokepoint_red OR CORRIDOR_FRAGILITY > θ_corridor_fragility_red:
  FENCE: BYPASS + LOCAL BUFFERS + COUPLING_REDUCTION
  - Build bypass routes
  - Preposition buffers
  - Reduce dependency coupling
  RETEST: redundancy metrics + corridor fragility
------------------------------------------------------------
INTERACTOS (Multi-Actor Misperception / Escalation)
------------------------------------------------------------
IF MISPERCEPTION_PROB > θ_misperception_red:
  FENCE: VERIFICATION_UP + SIGNAL_CLARITY + COOLING
  - Increase verification channels
  - Reduce ambiguous actions
  RETEST: misperception estimate
IF ESCALATION_LADDER_POSITION > θ_escalation_ladder_red:
  FENCE: COOLDOWN_WINDOW (ChronoHelmAI enforced)
  - Freeze provocative moves
  - Force de-escalation corridor
  RETEST: ladder position downshift
END_FILE

FILE_ID: CIVOS_FILE_CALIBRATION_PROTOCOL_THETA_v1
Title: Theta Calibration Protocol (Canonical)
Slug: /civos-runtime-theta-calibration-protocol-v1/
Applies: All nodes using ThetaPacks
GOAL
Convert default thresholds into local truth (node-specific) with minimal effort.
------------------------------------------------------------
Step 0 — Choose baseline window
------------------------------------------------------------
- Z1: 4 weeks OR 8 sessions/cycles (whichever is larger)
- Z2: 4–6 weeks OR 8 cycles
- Z3: 6–8 weeks OR 8 cycles
- Z5: 8–12 weeks OR 8 cycles
------------------------------------------------------------
Step 1 — Collect baseline sensor data
------------------------------------------------------------
For each sensor s:
- record value + timestamp + source
- keep notes on “real incidents” (failures, complaints, surprise events)
------------------------------------------------------------
Step 2 — Compute baseline bands (p10/p90)
------------------------------------------------------------
For each sensor s:
- p10_s = 10th percentile of baseline
- p90_s = 90th percentile of baseline
If p90_s ≈ p10_s (flat sensor):
- mark sensor as "low variance" and use absolute rule thresholds instead
- or replace sensor with higher-signal proxy
------------------------------------------------------------
Step 3 — Normalize into [0,1]
------------------------------------------------------------
For each sensor s at time t:
norm_s(t) = clamp((s(t) - p10_s)/(p90_s - p10_s), 0, 1)
Polarity note:
- If “GOOD when HIGH” (e.g., OBS_COVERAGE), keep as is.
- If “BAD when HIGH”, keep as is (higher = worse).
- Do NOT invert; interpret bands accordingly.
------------------------------------------------------------
Step 4 — Apply Z-level ThetaPack defaults
------------------------------------------------------------
Use the corresponding Z-level ThetaPack (Z1/Z2/Z3/Z5).
- GREEN: inside stable band
- AMBER: trigger ERCO repair (stitch/truncate plan)
- RED: trigger Fence stop-loss (freeze/localize/audit/redesign)
------------------------------------------------------------
Step 5 — Validate against real incidents
------------------------------------------------------------
Look for:
A) False negatives:
- incidents happened while sensors were GREEN
Action:
- tighten: move amber/red thresholds earlier by 0.05–0.10 for the relevant sensor(s)
B) False positives:
- sensors always AMBER/RED but no incidents or outcomes stable
Action:
- loosen: move thresholds later by 0.05 (max 0.10 per revision)
------------------------------------------------------------
Step 6 — Compound drift rule (mandatory)
------------------------------------------------------------
If:
- any 2 sensors are AMBER for 2 cycles
OR
- the same sensor is AMBER for 3 cycles
THEN:
- treat as RED and trigger Fence stop-loss
------------------------------------------------------------
Step 7 — Version forward
------------------------------------------------------------
Never overwrite:
- THETAPACK_*_v1 → THETAPACK_*_v1.1 → v1.2
Record:
- what changed
- why
- which incidents justified it
------------------------------------------------------------
Step 8 — Retest cadence
------------------------------------------------------------
- Z1: weekly
- Z2: biweekly
- Z3: monthly
- Z5: monthly/quarterly (but event-driven immediate runs)
END_FILE

FILE_ID: CIVOS_FILE_SENSOR_DICT_SCHEMA_v1
Title: SENSOR_DICT Schema (Canonical)
Version: v1.0
Applies: HCCP v1.0, ThetaPacks v1.x, ERCO, FenceOS, ChronoHelmAI
Goal: Every node uses the same sensor keys + metadata so runtime is executable.
========================================================
1) Top-level object
========================================================
SENSOR_DICT:
  META:
    SchemaVersion: "SENSOR_DICT_SCHEMA_v1"
    NodeID: <string>
    ZoomZ: <Z0..Z6>
    PhaseP_Estimate: <P0..P3>
    Timestamp: <ISO8601>
    Cadence: <daily|weekly|biweekly|monthly|event>
    SourceNotes: <string>
    BaselineWindow:
      Start: <date>
      End: <date>
  SENSORS:
    <SENSOR_KEY>: SENSOR_RECORD
    <SENSOR_KEY>: SENSOR_RECORD
    ...
  DERIVED:
    <DERIVED_KEY>: DERIVED_RECORD
  EVENTS:
    - EVENT_RECORD
  THRESHOLDS:
    ThetaPackID: <string>
    Bands: <GREEN/AMBER/RED results per sensor>
  ACTION_LOG:
    - ACTION_RECORD
========================================================
2) SENSOR_RECORD (per sensor)
========================================================
SENSOR_RECORD:
  value_raw: <number|string>
  unit: <string|null>
  polarity: <GOOD_WHEN_HIGH|BAD_WHEN_HIGH>
  source: <human|system|survey|audit|log|estimate>
  confidence: <low|medium|high>
  trend:
    direction: <up|down|flat|unknown>
    slope: <number|null>          # optional
    window: <string>              # e.g. "7d", "4w", "8cycles"
  baseline:
    p10: <number|null>
    p90: <number|null>
  normalized:
    value_norm: <0..1|null>       # computed if p10/p90 exist
    method: "p10p90_clamp_v1"      # fixed method name
  notes: <string|null>
========================================================
3) DERIVED_RECORD (computed metrics)
========================================================
DERIVED_RECORD:
  formula: <string>               # human-readable
  inputs: [<SENSOR_KEY>, ...]
  value: <number>
  unit: <string|null>
  confidence: <low|medium|high>
========================================================
4) EVENT_RECORD (ground truth anchors)
========================================================
EVENT_RECORD:
  event_id: <string>
  type: <incident|surprise|complaint|failure|success|shock|audit_find>
  timestamp: <ISO8601>
  severity: <low|medium|high>
  description: <string>
  linked_sensors: [<SENSOR_KEY>, ...]
  outcome: <resolved|ongoing|unknown>
  notes: <string|null>
========================================================
5) ACTION_RECORD (what you actually did)
========================================================
ACTION_RECORD:
  action_id: <string>
  timestamp: <ISO8601>
  trigger: <SENSOR_KEY or ThetaID or "compound_drift_rule">
  band: <AMBER|RED>
  actuation: <FREEZE|PROBE|LOCALIZE|AUDIT|REDESIGN|BYPASS|BUFFER|COOLDOWN>
  owner_role: <ARC|VIS|ORC|OPR>
  module: <OBSOS|REALITYOS|ACTOS|INCOS_CAPOS|CAPGRAPHOS|EXLEDGEROS|TOPOOS|INTERACTOS>
  retest_due: <ISO8601|null>
  exit_condition: <string>
  notes: <string|null>
========================================================
6) Canonical sensor keys (HCCP v1.0)
========================================================
--- OBSOS ---
OBS_COVERAGE:
  polarity: GOOD_WHEN_HIGH
  unit: "ratio"
SIGNAL_LATENCY:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
BIAS_INDEX:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
DECEPTION_INDEX:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
SURPRISE_RATE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
--- REALITYOS ---
SHARED_REALITY_GAP:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
TRUST_DECAY_RATE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
CONTRADICTION_DENSITY:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
MEME_R0:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
NIT_SCORE:
  polarity: BAD_WHEN_HIGH
  unit: "ratio"         # 0..1, 1 = crossed
--- ACTOS ---
T_ENFORCE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
ENFORCEMENT_THROUGHPUT:
  polarity: GOOD_WHEN_HIGH
  unit: "normalized"
COST_ENFORCE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
EVASION_RATE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
LEGITIMACY_DAMAGE_RATE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
--- INCOS+CAPOS ---
INCENTIVE_ALIGNMENT_SCORE:
  polarity: GOOD_WHEN_HIGH
  unit: "normalized"
CAPTURE_INDEX:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
GOODHART_PRESSURE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
RENT_SEEK_RATE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
PRINCIPAL_AGENT_GAP:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
--- CAPGRAPHOS ---
BOTTLENECK_CRITICALITY:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
SPOF_COUNT:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
DEPENDENCY_DEPTH:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
DIFFUSION_HALF_LIFE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
TRAINING_THROUGHPUT:
  polarity: GOOD_WHEN_HIGH
  unit: "normalized"
--- EXLEDGEROS ---
MAINTENANCE_BACKLOG:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
DEFERRED_DAMAGE_RATE:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
EXTERNALITY_LOAD:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
TRUE_NET_REGEN:
  polarity: GOOD_WHEN_HIGH
  unit: "normalized"
--- TOPOOS ---
CHOKEPOINT_INDEX:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
ROUTE_REDUNDANCY:
  polarity: GOOD_WHEN_HIGH
  unit: "normalized"
DISTANCE_FRICTION:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
CORRIDOR_FRAGILITY:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
--- INTERACTOS ---
MISPERCEPTION_PROB:
  polarity: BAD_WHEN_HIGH
  unit: "ratio"
ESCALATION_LADDER_POSITION:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
RETALIATION_LATENCY:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
CREDIBLE_COMMITMENT_SCORE:
  polarity: GOOD_WHEN_HIGH
  unit: "normalized"
--- AVOO Choice Budget (optional, but recommended) ---
RHO_CHOICE_OPR:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
SHEAR_PROXY:
  polarity: BAD_WHEN_HIGH
  unit: "normalized"
========================================================
7) Derived keys (recommended)
========================================================
DERIVED_KEYS_RECOMMENDED:
- COMPOUND_DRIFT_FLAG:
    formula: "1 if (>=2 sensors AMBER for 2 cycles) or (same sensor AMBER 3 cycles) else 0"
- HCCP_RISK_SCORE:
    formula: "max(RED_count*1.0, AMBER_count*0.5) capped to [0,1]"
- TTC_PROXY:
    formula: "function of SURPRISE_RATE, BOTTLENECK_CRITICALITY, BACKLOG slope"
- NET_STABILITY_MARGIN:
    formula: "TRUE_NET_REGEN - DAMAGE_RATE_PROXY (if you maintain Ḋ proxy)"
========================================================
8) Minimal example (EDUKATE node)
========================================================
EXAMPLE_SENSOR_DICT_MIN_v1:
META:
  SchemaVersion: "SENSOR_DICT_SCHEMA_v1"
  NodeID: "INST:SGP:SGP:BTM:EDUKATE"
  ZoomZ: "Z1"
  PhaseP_Estimate: "P2"
  Timestamp: "2026-02-23T00:00:00+08:00"
  Cadence: "weekly"
SENSORS:
  OBS_COVERAGE:
    value_raw: 0.62
    unit: "ratio"
    polarity: "GOOD_WHEN_HIGH"
    source: "estimate"
    confidence: "medium"
    trend: {direction:"down", slope:null, window:"4w"}
    baseline: {p10:0.55, p90:0.80}
    normalized: {value_norm:0.28, method:"p10p90_clamp_v1"}
  NIT_SCORE:
    value_raw: 0.30
    unit: "ratio"
    polarity: "BAD_WHEN_HIGH"
    source: "survey"
    confidence: "low"
    trend: {direction:"up", slope:null, window:"4w"}
    baseline: {p10:0.05, p90:0.60}
    normalized: {value_norm:0.45, method:"p10p90_clamp_v1"}
THRESHOLDS:
  ThetaPackID: "THETAPACK_EDUKATE_Z1_HCCP_CORE_v1"
  Bands: {OBS_COVERAGE:"AMBER", NIT_SCORE:"GREEN"}
END_FILE