method-audit

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Extract and compare data-collection methods across a set of empirical papers. Use when the user needs a cross-paper methods matrix or wants to assess how a literature gathers evidence.

Data & Documents 144 stars 27 forks Updated 3 days ago MIT

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# Method Audit > Reverse-engineer the data collection and empirical methods across a corpus of papers. Produce a critical comparison table that surfaces methodological blind spots. ## Output Path Per `rules/review-artefact-routing.md` (auto-loads in research projects (path-scoped to `paper-*/` and `paper/`)): - **Source slug:** `method-audit` - **Write reports to:** `reviews/_project/method-audit/<YYYY-MM-DD-HHMM>.md` inside the project. Path is relative to the research project root, not the Task-Management repo. - **Never** at project root (`./CRITIC-REPORT.md`-style filenames are forbidden — pre-rule layout). - **Idempotency:** timestamps include hour+minute (HHMM) to disambiguate same-day runs; never overwrite an earlier run's report. - **Index update:** if `reviews/INDEX.md` exists, write a one-line entry under "Latest per source" pointing at the new file. Otherwise `review-recap` will rebuild the index next time it runs. - **Infrastructure repos** (Task-Management, atlas-workspace, etc.): this section does not apply — the path-scoped rule won't load there. ## When to Use - Writing a methodology section — need to justify your approach relative to the literature - Reviewing empirical papers — need to compare data quality across studies - Identifying methodological gaps — what approach has nobody tried yet? - Preparing a replication or extension — need to understand exactly how prior work was done ## When NOT to Use - **Theoretical papers** — use an installed theor...

Details

Author
flonat
Repository
flonat/flonat-research
Created
7 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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