Github-research-plugin document-findings

Write GitHub research findings into a planning/ folder in the current repository, always date-stamped so results stay interpretable as the tooling landscape evolves. Creates planning/ if it does not already exist. Records the exact gh queries used so the research is reproducible.

install
source · Clone the upstream repo
git clone https://github.com/danielrosehill/github-research-plugin
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/danielrosehill/github-research-plugin "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/document-findings" ~/.claude/skills/danielrosehill-github-research-plugin-document-findings && rm -rf "$T"
manifest: skills/document-findings/SKILL.md
source content

Document GitHub Research Findings

The tooling landscape on GitHub evolves quickly — a top project today may be abandoned in six months, and new entrants appear constantly. Any research write-up must be date-stamped so future readers (including future-you) know the context in which the recommendation was made.

When to use

Trigger phrases include:

  • "Save these findings"
  • "Document this research"
  • "Write this to the planning folder"
  • "Add a note in the repo about this research"

Procedure

1. Locate or create the planning folder

In the current repository (working directory), look for one of:

  • planning/
  • docs/planning/
  • .planning/

If none exist, create

planning/
at the repo root.

Inside the planning folder, create or reuse a subfolder:

planning/github-research/

This keeps research artefacts grouped and out of the way of general planning docs.

2. Name the file with the date

File naming convention:

planning/github-research/YYYY-MM-DD-<short-topic-slug>.md

Examples:

  • planning/github-research/2026-04-16-mcp-server-frameworks.md
  • planning/github-research/2026-04-16-markdown-to-pdf-cli.md

Use

date +%Y-%m-%d
to get today's date — never hard-code a year.

If a file for the same topic already exists on the same date, append a short suffix (e.g.

-v2
) rather than overwriting.

3. Write the document

Use this template:

# GitHub Research: <Topic>

**Research date:** YYYY-MM-DD
**Researcher:** Claude Code (github-research plugin)
**Goal:** <one-sentence statement of what the user was trying to find / decide>

> ⚠️ Note on freshness: GitHub's tooling landscape evolves quickly. Findings below reflect repository state on the research date. Re-run the queries before acting on recommendations more than ~3 months old, especially for AI/ML projects.

## Queries run

Exact `gh` / `gh api` commands used, so the research is reproducible:

```bash
<paste each command>

Top candidates

RepoStarsLast pushOpen issuesLicenseLanguageNotes
owner/repo1.2k3 days ago14MITPythonActive, strong CI
.....................

Detailed evaluation

owner/repo

  • Verdict: recommend / maybe / avoid
  • Strengths: ...
  • Concerns: ...
  • Fit for our use case: ...

(Repeat per candidate)

Recommendation

<Concrete, opinionated recommendation. Which to try first, or "none are a good fit — build from scratch, here's why".>

Open questions / follow-ups

  • <things the user should check before committing>

### 4. Commit hygiene (do not auto-commit)

Write the file only. Do **not** run `git add` / `git commit` unless the user explicitly asked. Let the user review the document first.

After writing, report the path of the created file so the user can open it.

### 5. Link back from the repo's CLAUDE.md (optional)

If the repo has a `CLAUDE.md` and the user indicates this research will inform ongoing work, offer (don't auto-apply) to add a line under a "Prior research" section:

```markdown
## Prior research
- [YYYY-MM-DD: <Topic>](planning/github-research/YYYY-MM-DD-<slug>.md)

Guidance

  • Always include the date in both the filename and the document body. The whole point of this skill is reproducibility across time.
  • Always include the exact queries run. Without them the findings cannot be re-verified when they age.
  • Be honest about limits. If the search was narrow, say so. If results were sparse, say so. Do not invent projects to pad the list.
  • Prefer opinionated recommendations over neutral catalogues. The user asked for research to make a decision, not a Wikipedia article.