Research

Research

Source-backed research for documentation, API migration, paper, or state-of-the-art questions.

Input Schema

{
  "question": "required research question",
  "mode": "docs|sota|paper|methodology|code-fidelity",
  "constraints": [
    "optional codebase, compute, version, or implementation constraints"
  ],
  "done_when": "recommendations are source-backed with caveats and confidence"
}

Workflow

01: Create run directory

Run python PLUGIN_ROOT/shared/create_run.py --skill research once. Retain its single printed path as <run-directory> and substitute that literal path into every later artifact path and helper argument. Never store or reuse the path through a shell variable; shell variables do not persist across tool calls.

02: Define research question, mode, and constraints

Modes:

• docs: current API/docs/migration answer.
• sota: method comparison and implementation recommendation.
• paper: single-paper analysis.
• methodology: experiment design, metric, guard, and ablation review.
• code-fidelity: compare paper/spec claims against implementation.

03: Gather sources

Write <run-directory>/sources.md:

| Source | Type | Date/version | Why reliable | Used for |
| --- | --- | --- | --- | --- |

Source rules:

• Prefer primary docs, papers, specs, release notes, code.
• Use current live sources for volatile docs, dependencies, APIs.
• Mark stale/unavailable source explicitly.
• Do not cite secondary summaries for high-impact claims unless independently corroborated.

For sota, paper, methodology, code-fidelity, apply ../../shared/specialist-orchestration.md when independent expertise improves correctness. Write <run-directory>/specialist-research-plan.md with context packs for:

• web-explorer: current docs, release notes, API and dependency changes.
• scientist: formulas, methodology, metrics, ablations, benchmark claims.
• solution-architect: implementation fit, API boundaries, migration shape.
• squeezer: performance or resource claims.
• data-steward: datasets, splits, leakage, reproducibility.
• challenger: unsupported recommendation or overconfident source synthesis.

Do not send full papers, repositories, or all search results to every specialist. Give each only source excerpts, code files, questions needed for its axis.

04: Map to codebase context when implementation is relevant

Inspect python PLUGIN_ROOT/shared/collect_diff.py --help; collect working-tree scope into <run-directory>/baseline. Run topic scan separately; record unavailable paths/collection failures as evidence gaps.

Structural context (optional): for sota/code-fidelity questions naming a Python module/symbol, also probe codemap-py once: python PLUGIN_ROOT/shared/codemap_adapter.py context --category analysis [--target <qname>] --out <run-directory>/codemap-context.json. Per ../../shared/codemap-contract.md, absence/incompatibility is non-fatal — continue with the codebase mapping above. Persist the result once here; any specialist context pack from step 03 includes <run-directory>/codemap-context.json, never a fresh query.

05: Produce <run-directory>/research.md with:

• Question
• Constraints
• Source Table
• Findings
• Comparison for SOTA/method choices
• Implementation Fit
• Risks And Unknowns
• Recommendation
• Next Checks

06: For paper/code-fidelity mode, include dimensions:

• F: formula/math match
• H: hyperparameter parity
• E: evaluation protocol
• N: notation and naming consistency
• C: citation/derivation chain

07: Run review gate

Run git diff --check as an argv command. Write its combined output to <run-directory>/review.txt and retain its exit status as review evidence; do not erase a nonzero result.

08: Run shared gates and write the validated result artifact

Follow ../../shared/helper-cli-contract.md and authoritative help. For research-only work, mark lint, format, types, tests inapplicable with concrete reasons; review requires non-empty research.md, sources.md, clean diff check. Write RESEARCH_METADATA, validate as research, promote only validated candidate.

Replace explicit skip with relevant command when research includes executable validation.

Fail-Fast Rules

1. Missing question => fail.
2. No primary sources for high-impact/current claims => fail.
3. Recommendation not tied to constraints => fail.
4. Paper/code-fidelity claim without code or source reference => fail.
5. Result artifact missing => fail.

Quality Gates

Required:

• review: source table, caveats, self-review, git diff --check.

Conditional:

• tests: when research includes an executable validation or code-fidelity probe.

Calibration Hooks

On source-protocol/recommendation-policy change, update calibration:

• behavioral cases: stale docs, unsupported SOTA claim, paper-code mismatch
• benchmark patterns: research

Output Contract

Use shared gate schema from ../../shared/quality-gates.md.

Minimum artifact payload template: result-template.json.