chore: track claude skills, tools, templates, reference code and research-wiki
- Add all claude skills (brainstorming, commit, debugging, TDD, etc.) - Add claude hooks (pre-commit-guard, post-edit-quality) - Add research templates (experiment plan, research brief, etc.) - Add claude tools (arxiv/semantic_scholar/openalex fetch, wiki, exa) - Add TRM4 reference implementation as algorithm fidelity baseline - Add research-wiki content (plans, index, graph, query_pack) - Update .gitignore to exclude .graphify_version runtime state
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# graphify reference: add a URL and watch a folder
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Load this when the user ran `/graphify add <url>` or passed `--watch`. Neither is part of the default build.
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## For /graphify add
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Fetch a URL and add it to the corpus, then update the graph.
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```bash
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$(cat graphify-out/.graphify_python) -c "
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import sys
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from graphify.ingest import ingest
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from pathlib import Path
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try:
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out = ingest('URL', Path('./raw'), author='AUTHOR', contributor='CONTRIBUTOR')
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print(f'Saved to {out}')
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except ValueError as e:
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print(f'error: {e}', file=sys.stderr)
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sys.exit(1)
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except RuntimeError as e:
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print(f'error: {e}', file=sys.stderr)
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sys.exit(1)
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"
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```
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Replace `URL` with the actual URL, `AUTHOR` with the user's name if provided, `CONTRIBUTOR` likewise. If the command exits with an error, tell the user what went wrong - do not silently continue. After a successful save, automatically run the `--update` pipeline on `./raw` to merge the new file into the existing graph.
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Supported URL types (auto-detected):
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- YouTube / any video URL → audio downloaded via yt-dlp, transcribed to `.txt` on next run (requires `pip install 'graphifyy[video]'`)
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- Twitter/X → fetched via oEmbed, saved as `.md` with tweet text and author
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- arXiv → abstract + metadata saved as `.md`
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- PDF → downloaded as `.pdf`
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- Images (.png/.jpg/.webp) → downloaded, Claude vision extracts on next run
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- Any webpage → converted to markdown via html2text
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---
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## For --watch
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Start a background watcher that monitors a folder and auto-updates the graph when files change.
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```bash
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python3 -m graphify.watch INPUT_PATH --debounce 3
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```
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Replace INPUT_PATH with the folder to watch. Behavior depends on what changed:
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- **Code files only (.py, .ts, .go, etc.):** re-runs AST extraction + rebuild + cluster immediately, no LLM needed. `graph.json` and `GRAPH_REPORT.md` are updated automatically.
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- **Docs, papers, or images:** writes a `graphify-out/needs_update` flag and prints a notification to run `/graphify --update` (LLM semantic re-extraction required).
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Debounce (default 3s): waits until file activity stops before triggering, so a wave of parallel agent writes doesn't trigger a rebuild per file.
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Press Ctrl+C to stop.
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For agentic workflows: run `--watch` in a background terminal. Code changes from agent waves are picked up automatically between waves. If agents are also writing docs or notes, you'll need a manual `/graphify --update` after those waves.
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