assumption-graph-loop

name	assumption-graph-loop
description	Autonomous belief-revision loop — fuse @ai: annotations + /deep-research claims into the temporal assumption graph and revise the persistent belief log over time

Assumption-Graph Loop

One turn of the longitudinal belief loop for the temporal assumption graph (crates/ix-assumption-graph, contract docs/contracts/2026-05-31-assumption-graph.contract.md):

@ai: annotations ─┐
                  ├─► fuse (ix-fuzzy, Belnap C synthesis) ─► revise ─► belief-events.jsonl
research claims ──┘        cross-source only                 (append on verdict change)

It ingests the workspace's @ai: annotations plus any research-domain claims, fuses each claim's evidence, and appends a BeliefEvent for every claim whose verdict changed since the last run. Re-running on unchanged evidence is a no-op — so it is safe to schedule.

When to Use

• On a schedule (daily / weekly), to keep the belief log current as code and research evolve — the "semantic story over a long period".
• After a /deep-research run, to fold its verified findings into the graph and detect where new evidence contradicts a standing assumption.
• Before a review, to surface escalated (Contradictory) claims.

Run It

cargo run -p ix-assumption-graph --bin ix-assumption-graph-loop -- \
  --workspace .                                   \
  --research state/assumptions/research-claims.json   \  # optional
  --log     state/assumptions/belief-events.jsonl     \
  --trigger deep-research-reverify

Defaults: --workspace ., --log state/assumptions/belief-events.jsonl, --trigger loop, no research file. The log is created (with parent dirs) if absent. Output reports node count, total/appended belief events, and each flip (T -> C, etc.).

The research-claims.json shape

A JSON array. The truth-value judgment — mapping a verified finding to a hexavalent value — is the adapter's responsibility, NOT the crate's, so this file is the seam between /deep-research's output and the graph:

[
  {
    "claim": "p99 latency under 5ms",
    "truth_value": "F",
    "confidence": 0.85,
    "source": "deep-research",
    "evidence": "arxiv:2510.11822"
  }
]

• truth_value: one of T P U D F C (hexavalent).
• confidence: 0.0–1.0.
• source (optional, default "deep-research"): the independence class. Distinct sources are what let fusion synthesize a contradiction — give genuinely independent runs distinct source labels; do NOT relabel correlated re-runs as independent (contract §7.1 — over-counting).
• evidence (optional): a confirmed-real citation.

Converting a /deep-research run → research-claims.json

/deep-research returns result.findings[] (with claim, confidence high/medium/low, vote, sources) and result.refuted[]. Suggested mapping:

deep-research	truth_value	confidence
confirmed finding, confidence high	T	0.85–0.95
confirmed finding, confidence medium	P	0.6–0.75
confirmed finding, confidence low	U	~0.4
refuted[] entry	F	by vote margin

Fail-closed (contract §7.2): a multi-judge panel confirms well but catches invalidity poorly (~96% TPR / <25% TNR). Treat panel agreement as a gate to promote, and let any credible dissent push to U/D/C — never relabel correlated judges as independent sources. Verify every cited source resolves before writing it as evidence (deep-research has hallucinated arXiv ids).

Scheduling

Wrap the command in your scheduled-runner of choice (cron, the octo:schedule skill, or a state/-driven local runner like the adversarial-qa runner). Commit state/assumptions/belief-events.jsonl if you want the belief story versioned; otherwise treat it as regenerable local state.

What it does NOT do

• It does not invoke /deep-research itself — produce research-claims.json first (a /deep-research run + the mapping above), then run the loop.
• It does not run tests to verify code assumptions — feed test outcomes as additional @ai: annotation reconciliation or research claims.