Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add OneWave-AI/claude-skills --skill meeting-intelligencegit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/meeting-intelligence)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/meeting-intelligence"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/meeting-intelligence/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/onewave-ai/claude-skills/meeting-intelligence"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/meeting-intelligence.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 | $0.00044 | $0.01026 |
| Opus 5 | $0.00022 | $0.00513 |
| Sonnet 5 | $0.00009 | $0.00205 |
| Haiku 4.5 | $0.00004 | $0.00103 |
Grade A, and why
meeting-intelligence-system 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 9d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Intelligence System
Transform meeting transcripts into actionable insights, decisions, and follow-ups.
When to Use This Skill
Activate when the user:
- Provides a meeting transcript or recording
- Asks to "analyze this meeting"
- Needs action items extracted from notes
- Wants to generate meeting minutes
- Asks for decisions made in a meeting
- Needs a follow-up email created
- Mentions meeting notes or transcripts
Instructions
-
Extract Meeting Metadata
- Identify meeting title/topic
- Note participants (if mentioned)
- Determine meeting date/time (if available)
- Identify meeting type (standup, planning, retrospective, etc.)
-
Identify Decisions Made
- Extract all explicit decisions
- Note who made each decision (if clear)
- Include rationale for decisions (if stated)
- Flag tentative decisions vs. final decisions
- Note decisions that need follow-up approval
-
Extract Action Items
- List all tasks assigned or volunteered
- Identify owner for each action item
- Note deadlines or timeframes mentioned
- Flag action items without clear owners
- Prioritize action items (if priority discussed)
- Note dependencies between action items
-
Identify Blockers and Risks
- Extract mentioned blockers
- Note risks or concerns raised
- Identify unresolved issues
- Flag items needing escalation
- Note resource constraints mentioned
-
Analyze Discussion Sentiment
- Gauge overall meeting tone (productive, tense, confused, aligned)
- Identify areas of agreement and disagreement
- Note team morale indicators
- Flag conflict or tension points
-
Extract Key Topics Discussed
- Summarize main discussion points
- Note questions raised
- Identify topics needing follow-up
- Highlight important context or background
-
Generate Follow-Up Communications
- Create meeting minutes/summary
- Draft action item tracking email
- Suggest calendar invites for follow-ups
- Recommend next steps
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.
- 9d ago First seen · 150 lines · 44 tokens per session scan A 93fb8641b206
meeting-intelligence-system is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,026 once invoked, about $0.0002 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 2026-09-03.
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