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 agentmods add skills/jayrha/agentskills/meeting-summarizernpx skills add JayRHa/AgentSkills --skill meeting-summarizergit clone --depth 1 https://github.com/JayRHa/AgentSkillsWrote 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/jayrha/agentskills/meeting-summarizer)<a href="https://agentmods.dev/skills/jayrha/agentskills/meeting-summarizer"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/meeting-summarizer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00128 | $0.01564 |
| Opus 5 | $0.00064 | $0.00782 |
| Sonnet 5 | $0.00026 | $0.00313 |
| Haiku 4.5 | $0.00013 | $0.00156 |
Grade A, and why
meeting-summarizer 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 5d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Summarizer
Overview
This skill converts messy meeting input (chat transcripts, dictated notes, bullet dumps, recording transcripts) into a structured, decision-oriented summary that a busy reader can absorb in under a minute. The output prioritizes the two things people actually need after a meeting: what was decided and who owes what by when.
Keywords: meeting minutes, summary, recap, action items, decisions, owners, due dates, TLDR, standup, retro, 1:1, transcript, notes.
The non-negotiable rule: every action item must have an owner. If the source does not name one, the action item is flagged as OWNER: UNASSIGNED rather than silently dropped or guessed.
When To Use
Use this skill whenever the user wants raw meeting content distilled. Triggers include pasting a transcript, asking for "minutes", "a recap", "key takeaways", "next steps", or "the TLDR". Do not use it for live note-taking guidance or scheduling — only for processing content that already exists.
Process
Follow these steps in order.
-
Detect input type & length. Identify whether the input is a verbatim transcript (timestamps, speaker labels), shorthand notes, or a mixed dump. Note the approximate length so you can size the summary.
-
Identify metadata. Pull (or infer where stated) the meeting title/topic, date, and attendees. Never invent a date — if absent, omit it or write
Date: not stated. -
Extract the four content streams by scanning the whole input once for each:
- Decisions — anything settled, approved, chosen, or rejected. Look for trigger words: "we'll go with", "agreed", "approved", "decided", "let's do", "no to", "final".
- Action items — future work someone committed to. Look for: "I'll", "can you", "take", "follow up", "by Friday", "next step", assigned verbs.
- Discussion / context — the reasoning, options weighed, and notable points that aren't decisions or actions.
- Open questions / risks — unresolved items, blockers, parking-lot topics.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 119 lines · 128 tokens per session scan A 89d80fdee15b
meeting-summarizer is a skill published in the GitHub repository JayRHa/AgentSkills (4 stars, last pushed 1mo ago), licensed MIT. It adds 128 tokens to every session and 1,564 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
calle
Use CALL-E from Codex through the calle CLI. Use for CALL-E setup checks, authentication recovery, phone call planning, planned call execution, and call status checks.
codex-skin-pack-installer
Install Codex themes and Codex skin packs with npx skills. Use this skill when a user wants Codex to find, download, validate, apply, switch, remix, or restore Codex desktop themes such as caishen-readable, caishen-lite, mythic-guardian-noir, global-founder-bright, export-night, or caishen-max. It stages verified…
cost-aware-llm-pipeline
成本感知 LLM 管道，根据任务复杂度选择合适模型， 管理上下文预算，避免在长会话末尾做大型重构。.
meeting-notes
Paste raw meeting notes and get a clean summary with key decisions and action items.
appointo-automation
Automate Appointo tasks via Rube MCP (Composio). Always search tools first for current schemas.
beeminder-automation
Automate Beeminder tasks via Rube MCP (Composio). Always search tools first for current schemas.