substrate.json

{
  "version": 1,
  "summary": "Forge cognitive substrate wraps a frozen model with deterministic pre-action gates, repo state, memory, routing, impact simulation, and verification discipline.",
  "faculties": [
    { "id": "memory", "forge": "recall + cortex", "status": "partial", "guarantee": "facts and lessons are persisted as auditable files; relevance is advisory" },
    { "id": "learning", "forge": "cortex lessons", "status": "partial", "guarantee": "external outcomes update lesson confidence; no model weights are changed" },
    { "id": "imagination", "forge": "impact graph", "status": "operational-v1", "guarantee": "reverse dependency traversal predicts possible blast radius" },
    { "id": "self-correction", "forge": "verify + doom-loop guard", "status": "partial", "guarantee": "tests/builds are trusted over model claims" },
    { "id": "impact-awareness", "forge": "atlas + impact", "status": "operational-v1", "guarantee": "known symbols/files and likely dependents are surfaced before edits" }
  ],
  "mechanisms": [
    { "id": "M1", "name": "complexity-aware routing", "command": "forge route", "status": "solved-with-transparency-layer" },
    { "id": "M2", "name": "assumption gate", "command": "forge preflight", "status": "operational-v1" },
    { "id": "M3", "name": "task/session decomposition", "command": "forge scope", "status": "solved-with-boundary-helper" },
    { "id": "M4", "name": "goal anchoring", "command": "forge substrate", "status": "partial" },
    { "id": "M5", "name": "scope minimality", "command": "forge substrate", "status": "operational-v1-advisory" },
    { "id": "M6", "name": "inline verification", "command": "forge verify", "status": "partial" }
  ],
  "defaults": { "askThreshold": 0.6, "impactThreshold": 0.1 },
  "llm": {
    "enabled": false,
    "model": "haiku",
    "timeoutMs": 20000,
    "bidirectional": true,
    "minConfidence": 0.8,
    "signalFloor": 0.4,
    "note": "Opt-in (FORGE_LLM=1). The model PROPOSES; the deterministic rubric + repo grounding + tests VERIFY. Any failure falls back to the deterministic path — never blind, never blocking. `bidirectional` (default true) lets a verified reading also clear a false ask / route a tier down (to the voted band), never past the hard floors (`signalFloor`, repo grounding, no-anchor). Readings are compared verdict to verdict (ask vs proceed, band vs band), and a proposer flips the rubric only when it holds its own verdict with probability >= `minConfidence`. A model vote for a HIGHER tier is never applied (escalate only on a verifier failure); it is reported as an advisory `llm.escalateTo` that nothing acts on automatically. `minConfidence` is an a-priori conservative default, not fit to data - choose it on fresh labelled tasks. Set `bidirectional` false for the conservative mode (the model can only tighten the gate and never moves the tier)."
  },
  "policies": {
    "preAction": "Run substrate before ambiguous, expensive, multi-file, or mutating work.",
    "escalation": "Start with the cheapest capable tier and escalate only after an external verifier failure.",
    "hookEnforcement": "Block or warn only on deterministic risks; keep research-edge judgments advisory.",
    "honesty": "Label memory relevance, routing fit, and minimality as advisory unless verified by tests, graph membership, or explicit user scope."
  },
  "limits": [
    "Graph edges are static and approximate, not conservative: dependents can be missed (dynamic dispatch, generated code, unresolved imports), so an empty impact set means unknown, not safe.",
    "Memory and learning are external file-backed lessons, not weight-level learning.",
    "Non-hook editors receive advisory MCP/context only; Forge cannot enforce hooks where the host has no hook surface."
  ]
}