Hypothesis Gen

The loop

pool = the kept hypotheses (starts empty). gaps = open questions the LiteratureScout has surfaced (starts empty; seed from <question>). dry = consecutive rounds with no new keep (starts 0). <N> starts at 1.

Copy this checklist and tick items off:

• Generate — run roles/Generator.md (spawn-or-degrade) with <question>, the current pool, gaps, and <gen_n>; it writes round<N>/candidates.json (<gen_n> specific, testable, plausibly-novel candidates aimed at the gaps, none duplicating the pool).
• Ground — run roles/LiteratureScout.md (spawn-or-degrade) on candidates.json with <lit> and the <eval_scale> caps; it writes round<N>/litscout.json (validates schemas/litscout.schema.json) — per candidate: novelty + closest prior work, support, gap, testability, each citing real evidence.
• Judge — as roles/Judge.md, apply the fixed rubric + evidence gate to litscout.json, checking each candidate against the pool for duplicates; write round<N>/verdict.json (validates schemas/verdict.schema.json): scores, total, keep, duplicate_of.
• Update — add every keep:true non-duplicate to pool (with scores + grounding + how-to-test); add this round's gap points to gaps. If ≥1 new keep, dry = 0; else dry += 1.
• Log one ledger row (see Ledger); N = N + 1.
• Stop check — dry == <patience> (saturation) or N > <budget> → stop (see Stops).

Re-ground every round — novelty is judged from a fresh literature check each round, never carried over, so "the literature already covers this" reliably kills a crowded idea. Every cited snippet comes from a real retrieval that round; on {"error","fallback"} fall back to WebSearch/WebFetch — never invent a paper.

schemas/litscout.schema.json gates the LiteratureScout output — a generic instance:

{"round": 2,
 "evaluations": [{"hid": "r2h1", "novelty_assessment": "novel",
   "closest_prior_work": [{"claim": "X tested for facts, not skills", "cites": ["E1"]}],
   "support": [{"claim": "spacing aids motor consolidation", "cites": ["E2"]}],
   "gap": [{"claim": "long-term procedural retention untested at scale", "cites": ["E1"]}],
   "testability_note": "RCT: spaced vs massed schedule, 1-month retention."}],
 "evidence": [{"key": "E1", "title": "...", "source": "s2", "id": "a1b2", "snippet": "...verbatim..."}]}

schemas/verdict.schema.json gates the Judge output — a generic instance:

{"round": 2,
 "verdicts": [{"hid": "r2h1",
   "scores": {"novelty": 4, "grounding": 4, "testability": 5, "specificity": 4, "significance": 4},
   "total": 82.0, "keep": true, "gate_failures": [], "duplicate_of": null,
   "rationale": "Closest work shows X untested for skills -> novel; supported; clean RCT named."}]}

Ledger

<sandbox_root>/ledger.tsv, tab-separated, never commas in free text. Header:

round	generated	kept_new	pool_size	top_kept

Example:

round	generated	kept_new	pool_size	top_kept
1	6	3	3	spaced practice aids procedural (not just declarative) retention [82]
2	6	2	5	sleep-timed review beats time-of-day-matched review [78]
3	6	0	5	-

Per-round candidates.json / litscout.json / verdict.json live in round<N>/. Report the best state of the pool when stopping, not just the last round. Leave ledger.tsv, round*/, and literature/ untracked.

Constraints

• Never fabricate citations or snippets — every evidence entry is a real <lit>/WebFetch retrieval from that round, verbatim; the evidence gate exists to catch fabrication.
• Novelty is decided by the literature, not assertion — a hypothesis the search shows is already established is killed, however appealing; "I think it's novel" with no closest-work search caps novelty.
• Generate ≠ confirm — kept hypotheses are strong candidates to test, each stated with its test; never report them as established findings.
• The rubric is fixed and the keep-bar is stable across rounds, so saturation is a meaningful stop.
• Reward distinct hypotheses, not volume — duplicates and rewordings are cut.
• No installs — the sibling literature-search skill is stdlib-only; never print or commit API keys (keys.env stays gitignored at the project root). The sandbox is self-contained — no ../ escapes.
• Do not pause the loop to ask whether to continue; run until saturation or budget.

Stops

The loop stops on the first of:

• Saturation — dry == <patience> consecutive rounds add no new kept hypothesis.
• Budget — <budget> rounds reached.

End with the ranked hypothesis set (<report> path) — each hypothesis with its statement, novelty assessment + closest prior work (cited), supporting evidence (cited), the gap it fills, and how to test it — plus the pool-size trajectory from ledger.tsv and the strongest unexplored gaps, so the user sees both the vetted hypotheses and where a deeper run would look next.