autoresearch-db

name

autoresearch-db

description

Use when building the evidence base for a chosen autoresearch topic — maps the insight areas needed to propose new ideas, downloads references to cover them via download-ref, distills each area into research/INSIGHTS.md for user selection, builds a structured domain database and pinned reference implementations, and catalogs all algorithms/software in research/CATALOG.md. Owns the survey gate. Stage 2 of the autoresearch pipeline.

Autoresearch DB

Input: a topic with metrics in topics.md. Output: a knowledge base, an insight file, a domain database, pinned reference code, a catalog — and the survey gate passed. The point is not "papers exist on disk" but "the agent holds the insights needed to propose new ideas".

Procedure

1. Map insight areas. From the topic and its metrics, list the insight areas an idea-proposer needs: algorithmic techniques, proof/analysis methods, data structures, benchmark practices for this problem class. Show the list to the user before downloading anything.
2. Download for coverage. Acquire references with the download-ref skill into <project>/.knowledge/. Coverage check: every insight area is covered by ≥1 downloaded reference; areas with no coverage trigger further search/downloads. SOTA-results-only coverage is insufficient.
3. Distill. For each insight area, write one entry in research/INSIGHTS.md following skills/autoresearch-db/references/insights-template.md (Technique / Applies when / Limits / Sources). Distill from the rendered papers in .knowledge/, not from memory.
4. User selects. Present the distilled areas via AskUserQuestion (multi-select): which are needed for idea generation on this topic? Selected entries go under ## Selected, the rest under ## Shelved. The run loop draws only on Selected.
5. Domain database. Build the structured dataset the topic needs (e.g. QEC codes as JSON) under research/database/, with a README.md documenting schema and provenance of every record.
6. Pin reference implementations. For each key algorithm with public code: record URL + commit hash, build it, and run its own smoke test/example. Implement small reference versions only where no code exists and the algorithm is load-bearing.
7. Catalog. Write research/CATALOG.md: every algorithm/software relevant to the topic, one row each — name, source (paper/repo), status reproduced (we ran it) / pinned (source-locked, not yet run) / paper-only (no code exists), and notes.

Survey gate (owned by this skill)

Flip survey_gate: passed <date> and set stage: validator in research/STATE.md only when all of:

• research/CATALOG.md exists and every key algorithm from the insight map appears in it;
• .knowledge/INDEX.md lists every reference cited in INSIGHTS.md and CATALOG.md;
• research/INSIGHTS.md has a non-empty ## Selected section chosen by the user;
• every reproduced-status entry actually ran (its output is recorded in CATALOG.md notes).