Files
Video-Tree-TRM5/.claude/skills/graphify/references/add-watch.md
T
iomgaa 6bdb802f01 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
2026-07-06 20:59:03 -04:00

2.4 KiB

graphify reference: add a URL and watch a folder

Load this when the user ran /graphify add <url> or passed --watch. Neither is part of the default build.

For /graphify add

Fetch a URL and add it to the corpus, then update the graph.

$(cat graphify-out/.graphify_python) -c "
import sys
from graphify.ingest import ingest
from pathlib import Path

try:
    out = ingest('URL', Path('./raw'), author='AUTHOR', contributor='CONTRIBUTOR')
    print(f'Saved to {out}')
except ValueError as e:
    print(f'error: {e}', file=sys.stderr)
    sys.exit(1)
except RuntimeError as e:
    print(f'error: {e}', file=sys.stderr)
    sys.exit(1)
"

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.

Supported URL types (auto-detected):

  • YouTube / any video URL → audio downloaded via yt-dlp, transcribed to .txt on next run (requires pip install 'graphifyy[video]')
  • Twitter/X → fetched via oEmbed, saved as .md with tweet text and author
  • arXiv → abstract + metadata saved as .md
  • PDF → downloaded as .pdf
  • Images (.png/.jpg/.webp) → downloaded, Claude vision extracts on next run
  • Any webpage → converted to markdown via html2text

For --watch

Start a background watcher that monitors a folder and auto-updates the graph when files change.

python3 -m graphify.watch INPUT_PATH --debounce 3

Replace INPUT_PATH with the folder to watch. Behavior depends on what changed:

  • 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.
  • Docs, papers, or images: writes a graphify-out/needs_update flag and prints a notification to run /graphify --update (LLM semantic re-extraction required).

Debounce (default 3s): waits until file activity stops before triggering, so a wave of parallel agent writes doesn't trigger a rebuild per file.

Press Ctrl+C to stop.

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.