Borrowing it
Nothing to install: this file belongs to t0uchY233/telegram-summarize. 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/t0uchY233/telegram-summarize/main/.agents/skills/meeting-minutes/SKILL.mdgit clone --depth 1 https://github.com/t0uchY233/telegram-summarizeWrote 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/t0uchy233/telegram-summarize/meeting-minutes)<a href="https://agentmods.dev/skills/t0uchy233/telegram-summarize/meeting-minutes"><img src="https://agentmods.dev/badge/skills/t0uchy233/telegram-summarize/meeting-minutes/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/t0uchy233/telegram-summarize/meeting-minutes"><img src="https://agentmods.dev/badge/skills/t0uchy233/telegram-summarize/meeting-minutes.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00029 | $0.02624 |
| Opus 5 | $0.00015 | $0.01312 |
| Sonnet 5 | $0.00006 | $0.00525 |
| Haiku 4.5 | $0.00003 | $0.00262 |
Grade A, and why
meeting-minutes 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 11d 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.
This is a copy
84% identical to meeting-minutes — 58 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Minutes Skill — Short Internal Meetings
Purpose / Overview
This Skill produces high-quality, consistent meeting minutes for internal meetings that are 60 minutes or shorter. Output is designed to be clear, actionable, and easy to convert into task trackers (e.g., GitHub Issues, Jira). The generated minutes prioritize decisions and action items so teams can move quickly from discussion to execution.
Telegram Discussion Summary Mode
Use this mode when the source is a Telegram channel or group. It replaces the meeting-specific intake questions and the Strict Minutes Schema below: do not ask for an organizer, agenda, reviewer, action items, or a next meeting unless the Telegram messages themselves establish them.
The core unit of the summary is a topic with its participants, positions, humor, and resources kept together. This preserves the social context of the discussion instead of reducing it to an anonymous list of conclusions.
Topic block
Use this shape for every substantive topic:
### <Topic>
- **What was discussed:** <concise synthesis>
- **Active participants and positions:**
- @handle — <main claims, arguments, examples, or disagreement>
- **Outcome / disagreement:** <supported conclusion or unresolved split>
- **Resources:**
- <exact URL> — <why it mattered in this topic> — <source message link>
- **From the chat:**
> "<verbatim joke or meme quote>" — @handle, <reaction count>, <source message link>
Apply these rules:
- Attribute every topic. Name the people who materially advanced that topic and summarize the main thought each person contributed. Message volume alone does not make someone an active participant. A global participant table may supplement this, but never replace topic-level attribution.
- Use humor as evidence of the chat's tone. Quote a topical joke or meme verbatim when it naturally fits the topic. A context-free joke may appear in a separate
From the chatinterlude only when verified reaction metadata totals more than 4 reactions. Prefer the strongest 1–3 quotes across the whole summary so humor adds texture without taking over. - Never infer reactions. Show a reaction count only when the source payload provides it. If reaction metadata is unavailable, do not claim that a quote passed the reaction threshold and do not use it as a context-free interlude.
- Keep resources with their discussion. Place GitHub repositories, documentation, articles, tools, videos, and other links inside the topic where they were mentioned. Preserve URLs exactly and add the source Telegram message link when possible.
- Reserve a standalone resources section for orphan links. Use
Standalone resourcesonly for links posted without enough surrounding discussion to assign them to a topic. Do not duplicate topic resources there. - Preserve quotation fidelity. Do not rewrite, correct, sanitize, or merge a quoted joke. Keep it short, identify the author, and link the source message when possible.
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.
- 11d ago First seen · 292 lines · 29 tokens per session scan A 229558cdb37e
meeting-minutes is a skill published in the GitHub repository t0uchY233/telegram-summarize (0 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 2,624 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to meeting-minutes, differing in 58 lines, and is treated as a copy.
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