agentleFS
scholayscholay/skills/literature-discovery/SKILL.md

literature-discovery

Skill141 starsChanged 5 months agoMITView on GitHub

Systematically discover and shortlist academic literature for a research project. Use when building a reading corpus from scratch, expanding an existing one, filling topic or language gaps, or turning search results into a prioritized intake queue.

The file

We split this skill into the rules it gives an agent

10 rules. About 0 are common, 8 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈8

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Write one sentence: what is this research about, and what is it *not* about?

    line 16
  2. Distinctive:

    Do not start by downloading 200 results from a keyword search.

    line 37
  3. Distinctive:

    Keep a running candidate list.

    line 49
  4. Distinctive:

    Do not annotate or read deeply at this stage.

    line 57
  5. Distinctive:

    Before promoting items to intake, ask:

    line 61
  6. Very specific:

    Only keep-status items move to the next stage (source intake).

    line 68
  7. Distinctive:

    Search in waves. One wave = one seed's full expansion before starting the next seed.

    line 79
  8. Distinctive:

    Never download everything from a keyword search in one pass.

    line 80
  9. Distinctive:

    Keep translated titles and original titles together.

    line 82
  10. Very specific:

    Read references/search-matrix.md for a reusable matrix template and project-specific axis examples.

    line 88

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Literature Discovery

The core problem

Most researchers start by downloading everything that looks relevant. This creates an unmanageable pile with no structure and no sense of what's missing. The alternative: build the corpus in deliberate waves, starting from a small seed set and expanding outward in three directions.

Workflow

1. Define scope before searching

Write one sentence: what is this research about, and what is it not about? This sentence is your filter for every candidate you encounter.

Then build a search matrix:

AxisExamples
Topic termsmain concept + synonyms + older names
Region/contextgeographic or institutional scope
Object typewhat specific thing you're studying
Time periodhistorical range
Languageall relevant languages, not just English
Methodfield methods you're comparing against

2. Start from a seed set, not a broad search

Pick 3–5 items you already know are strong:

  • One overview or survey paper
  • One foundational monograph or book
  • One case-study cluster
  • One methods paper

Do not start by downloading 200 results from a keyword search.

3. Expand in three directions from each seed

Backward — who does this paper cite? Follow references to earlier foundational work.

Forward — who cites this paper? Use Google Scholar, Semantic Scholar, or OpenAlex to find later work building on it.

Lateral — what related terms or adjacent topics does this paper not cover? Search those gaps explicitly.

4. Record every candidate before annotating

Keep a running candidate list. Add a row for every item you encounter, even if you don't have the PDF yet. Minimum fields per row:

  • title, authors, year
  • source (where you found it)
  • language
  • status: candidate / keep / exclude / needs_pdf / needs_translation
  • reason (one line)

Do not annotate or read deeply at this stage.

5. Check for coverage bias

Before promoting items to intake, ask:

  • Am I over-representing one language, one region, one time period?
  • Are there practitioner sources, grey literature, or non-English materials I haven't touched?
  • What would a critic say is missing from this list?

6. Promote only strong items

Only keep-status items move to the next stage (source intake). Everything else stays in the candidate list with a reason recorded.

Output expectations

  • A reusable search matrix
  • A candidate list with statuses and one-line reasons
  • A gap list: what's under-covered and why
  • A keep queue ready for source intake

Rules

  • Search in waves. One wave = one seed's full expansion before starting the next seed.
  • Never download everything from a keyword search in one pass.
  • De-duplicate before promoting: DOI first, then title + year, then manual check.
  • Keep translated titles and original titles together.
  • Record the search URL and date for every batch — you will need to verify later.
  • A candidate list with 200 items and no statuses is not useful. Triage as you go.

References

  • Read references/search-matrix.md for a reusable matrix template and project-specific axis examples.

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.