github-import

name	github-import
description	Import GitHub starred repos into the Obsidian vault as individual notes with a .base database view. Fetches stars via gh CLI, creates new notes (with README summary in French, auto-tags) and updates existing notes (stars, forks, dates, topics) in Resources/GitHub-Stars/. Idempotent — safe to run repeatedly. Use this skill when the user wants to sync, import, update, or fetch their GitHub stars, or mentions starred repos, GitHub bookmarks, or gh stars.
argument_hint	[--all | --count N | --fix-dates | --strip-sections | --help]

GitHub Stars Import

Import GitHub starred repositories into the vault as individual structured Obsidian notes, with an Obsidian Bases database view for browsing, filtering, and sorting.

Trigger

/github-import — fetch last 30 stars (daily incremental) /github-import --all — fetch all stars (full sync) /github-import --count N — fetch N most recent stars /github-import --fix-dates — fix repo_updated on all existing files /github-import --strip-sections — remove Details/Topics sections from all files

Storage

• Individual notes: Resources/GitHub-Stars/<Owner>-<Repo>.md
• Database view: Resources/GitHub-Stars/GitHub-Stars.base
• Script: .claude/skills/github-import/gh_stars.py
• LLM manifest: /tmp/gh_stars_manifest.json

Architecture

The import is split into two phases to minimize LLM token usage:

1. Python script (mechanical) — fetches API data, generates frontmatter/Details/Topics/footer, writes all files, fetches READMEs. Outputs a manifest of repos needing French summaries.
2. LLM (intelligence) — reads the manifest, generates French summaries, injects them into ## Resume sections, and enriches ## Voir aussi cross-links.

Workflow

Phase 1 — Run the Python script

Run the script with the appropriate flags:

# Incremental (default): last 30
python3 .claude/skills/github-import/gh_stars.py

# Full sync
python3 .claude/skills/github-import/gh_stars.py --all

# Custom count
python3 .claude/skills/github-import/gh_stars.py --count 50

# Fix dates only (no new imports)
python3 .claude/skills/github-import/gh_stars.py --fix-dates

# Strip Details/Topics sections from all files
python3 .claude/skills/github-import/gh_stars.py --strip-sections

The script:

1. Fetches stars via gh CLI (paginated for --all)
2. Fetches GitHub Lists index via GraphQL
3. Classifies new vs existing stars
4. For each new star (in parallel, 10 workers):
   • Fetches last commit date on default branch (/repos/OWNER/REPO/commits?per_page=1)
   • Fetches and decodes README (truncated to 5000 chars)
   • Generates tags from language + topics using mapping rules
   • Writes the complete .md file with {{RESUME_PLACEHOLDER}} in the Resume section
5. For each existing star (in parallel):
   • Updates frontmatter (stars, forks, license, description, topics, lists, repo_updated, updated_at)
   • Re-derives tags (preserving user-added tags)
   • Does NOT touch Resume, Voir aussi, or footer
6. Creates .base file if missing
7. Writes manifest to /tmp/gh_stars_manifest.json

Report the script's output to the user, then proceed to Phase 2.

Phase 2 — LLM generates French summaries

Read /tmp/gh_stars_manifest.json. It's an array of objects:

[{
  "file": "owner-repo.md",
  "full_name": "owner/repo",
  "description": "...",
  "language": "Go",
  "readme": "decoded README content (max 5000 chars)"
}]

For each entry with a non-null readme:

1. Generate a French summary (3-8 sentences) covering: what the project does, key features, target audience, and why it's interesting
2. Replace {{RESUME_PLACEHOLDER}} in the file with the summary

For entries where readme is null, replace {{RESUME_PLACEHOLDER}} with (README non disponible).

Parallelization: Split the manifest into batches of ~30 and spawn one Agent per batch (run_in_background=true, mode=bypassPermissions). Each agent:

• Reads its batch from the manifest
• Generates French summaries
• Uses the Edit tool to replace {{RESUME_PLACEHOLDER}} in each file
• Reports count of summaries generated

This keeps the main context clean and parallelizes the only LLM-expensive work.

Phase 3 — Enrich Voir aussi cross-links

After all summaries are injected, enrich ## Voir aussi for new notes:

For each new star, find related stars among ALL existing notes in Resources/GitHub-Stars/:

1. Same owner: other repos by the same GitHub owner/org
2. Same language: repos in the same primary language (limit to 3)
3. Shared topics (≥2 in common): repos with overlapping GitHub topics

Keep to 3-6 links max per note. Use [[Owner-Repo]] wikilink format.

This can be done efficiently by grepping frontmatter fields to build an index, then batch-editing the Voir aussi sections.

Phase 4 — Report

Display a summary:

Import GitHub Stars terminé.
- Stars récupérées : Y
- Nouvelles : X
- Mises à jour : Z
- READMEs résumés : N (nouveaux uniquement)
- Notes créées : X
- Notes mises à jour : Z

Note Format

Each note in Resources/GitHub-Stars/<Owner>-<Repo>.md:

---
type: github-star
repo_fullname: "owner/repo"
repo_name: "repo"
owner: "owner"
description: "original description"
language: "Language"
stars: N
forks: N
license: "SPDX-ID"
topics: [topic1, topic2]
tags: [github-star, tag1, tag2]
lists: ["List A", "List B"]
homepage: "url"
source: "github_url"
starred_at: YYYY-MM-DD
repo_created: YYYY-MM-DD
repo_updated: YYYY-MM-DD
status: draft
created: YYYY-MM-DD
updated_at: YYYY-MM-DD
---

## Resume

<French summary — 3-8 sentences>

## Voir aussi

- [[Related-Star-1]]
- [[Related-Star-2]]

---
↑ [[GitHub-Stars]] | [[tag1]] | [[tag2]]

Tag Mapping Rules

Language → tag: Go → go, Python → python, TypeScript → typescript, JavaScript → javascript, Rust → rust, Java → java, etc. Use lowercase.

Topics → tags:

• cli, command-line → cli
• machine-learning, deep-learning, llm, ai → ai
• devops, ci-cd, infrastructure → devops
• kubernetes, docker, containers → devops
• security, cryptography → security
• database, sql, postgresql → database
• frontend, react, vue, svelte → frontend
• backend, api, rest, grpc → backend
• open-source → open-source
• startup, saas → startup
• Other topics: keep as-is if single lowercase words

Always include github-star. 3-8 tags total.

repo_updated Field

Do NOT use pushed_at or updated_at from the starred repos API — these reflect activity on ANY branch. The script fetches the last commit date on the default branch via:

gh api '/repos/OWNER/REPO/commits?per_page=1' --jq '.[0].commit.committer.date'

Fallback to pushed_at only if the commits API call fails.

Rules

• The gh CLI must be installed and authenticated. If not, tell the user to run gh auth login.
• README summaries are in French. Repo descriptions stay in their original language in frontmatter.
• File naming: <Owner>-<Repo>.md (keep GitHub's original casing).
• If README fetch fails, use (README non disponible).
• The .base file is only created once. It auto-updates via Obsidian's live queries.
• Content language: descriptions stay original, summaries and sections are in French.

Post-Import — Log

After reporting results, append one line to Areas/Claude/operations-log.md:

| YYYY-MM-DD HH:MM | ingest | github-import | X créées, Y maj | Resources/GitHub-Stars/ |

Use actual counts from the import. Create the file with header if it doesn't exist.

Examples

Input: /github-import → Runs script for 30 latest stars, then LLM generates summaries

Input: /github-import --all → Full sync of all stars

Input: /github-import --count 10 → Fetches and processes 10 latest stars

Input: /github-import --fix-dates → Fixes repo_updated on all existing files (no new imports)

Input: /github-import --strip-sections → Removes Details/Topics sections from all existing files