Menü
Fetch a public Loom video's transcript from its share link and summarize it.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
Audit and improve AGENTS.md files in repositories, keeping CLAUDE.md as a one-line @AGENTS.md reference so the same project memory works across tools (Claude Code, Codex, Gemini CLI, …). Use when user asks to check, audit, update, improve, or fix AGENTS.md (or CLAUDE.md) files. Scans for all such files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "AGENTS.md maintenance" or cross-tool "project memory optimization".
Graph a skill's flow — steps, artifacts, invocations — render it with draw-graphology, and report checkable weak links — each verified by two independent subagents — as a handoff file of lessons for improve-skills.
Summarize the CURRENT Claude session's work into a very concise 3P (Progress/Plans/Problems) Slack status report, draft it to the user for review, then place it as a native Slack draft for a final look before they send. User-invoked mid-session (`/slack-comm`) when you need to report what you just did in a tight, matter-of-fact format. Not for org-scale newsletters or pulling other people's updates.
Fold one lesson into one existing skill, behind a confirmation gate.
Unattended cleanup loop — scan the codebase for readability debt and run up to N targets (default 5) through a cleaner/reviewer/tester trio; verified cleanups land as per-target refactor commits on a clean-loop/<date> branch. Not a performance tool (pair-ratchet) and not for polishing just-written code (simplify-python).
Create data-driven network graph visualizations with graphology + sigma.js. Use when the user wants to visualize a network, dependency graph, knowledge graph, call graph, org/relationship map, communities/clusters, or any node-edge dataset too large to place by hand.
| name | loom-transcript |
| description | Fetch a public Loom video's transcript from its share link and summarize it. |
| disable-model-invocation | true |
Turn a Loom share link into its spoken transcript, then summarize. This skill only fetches; the summarizing is yours to do.
Get the link. Take the loom.com/share/… URL from the invocation. If none was given, ask for one.
Fetch the transcript. Run the bundled script from this skill's directory:
python3 loom_transcript.py "<url>"
Add --timestamps only when the user wants to navigate or cite moments in the video — it appends a segments array with per-line start times.
On error, stop. If the JSON has an error field, relay that message to the user verbatim and stop — there is no fallback. The common cause is a private/workspace-locked video, which cannot be read without the owner's credentials.
Summarize. By default, give a concise summary of the transcript (lead with the video's title). If the user stated how or what to summarize — a focus, a length, a format, "just the action items", "verbatim quote about X" — follow that instead of the default summary.
Done when the user has the summary (or the specific rendering they asked for), or a clear reason it couldn't be fetched.