Borrowing it
Nothing to install: this file belongs to luanmorenommaciel/agentspec. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/luanmorenommaciel/agentspec/main/.claude/skills/meeting-analysis/SKILL.mdgit clone --depth 1 https://github.com/luanmorenommaciel/agentspecWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/luanmorenommaciel/agentspec/meeting-analysis)<a href="https://agentmods.dev/skills/luanmorenommaciel/agentspec/meeting-analysis"><img src="https://agentmods.dev/badge/skills/luanmorenommaciel/agentspec/meeting-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/luanmorenommaciel/agentspec/meeting-analysis"><img src="https://agentmods.dev/badge/skills/luanmorenommaciel/agentspec/meeting-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00172 | $0.01816 |
| Opus 5 | $0.00086 | $0.00908 |
| Sonnet 5 | $0.00034 | $0.00363 |
| Haiku 4.5 | $0.00017 | $0.00182 |
Grade A, and why
meeting-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Analysis
Turn a meeting transcript into two shareable artifacts:
- A formal analysis document, produced by the
meeting-analystagent with its 10-section extraction framework (decisions, action items, requirements, blockers, implicit signals). - A short follow-up message, ready to paste into the team's chat channel.
Both artifacts are team deliverables. Hold them to that bar: formal, professional, content only — nothing about how the analysis was produced.
When to Use
- The user provides a meeting transcript (file path or pasted text) and wants it analyzed or summarized.
- The user asks to "analyze this meeting", "write up this meeting", or "summarize this for the team".
- The user wants a channel-ready post announcing meeting outcomes.
Skip If
- The user wants a daily standup message — that is the
standup-reportskill (this skill can feed it; see step 7). - The user only wants to store, file, or catalog a transcript, with no analysis requested.
Core Heuristic: TL;DR Inline, Extra Documents Only When Needed
- The inline TL;DR (1–2 lines) always goes in the follow-up message itself. It is the at-a-glance "what you need to know", without padding.
- A separate summary document is justified only for very long (3h+) or unusually dense meetings. For everything else, the analysis document is enough. More documents do not add more value.
Process
1. Gather Input and Context
Collect before delegating:
- Transcript — a file path or pasted text. If pasted, save it to a file first so the analyst agent can read it.
- Meeting purpose — what the meeting was for and, if the requester attended, what they say it resolved. This outcome lens tells the analyst where to focus.
- Participants — ask for a roster only if attribution matters for this meeting and the transcript leaves it unclear who said what. Machine transcripts often carry unreliable speaker labels; the requester's account of who attended and who decided beats the transcript. Do not interrogate the user when attribution is irrelevant to the outcomes.
- Working language — see step 2.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 165 lines · 172 tokens per session scan A cfd21e03329c
meeting-analysis is a skill published in the GitHub repository luanmorenommaciel/agentspec (246 stars, last pushed yesterday), licensed MIT. It adds 172 tokens to every session and 1,816 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
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