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 pattern-ai-labs/built-with-agentcall --skill meeting-standupgit clone --depth 1 https://github.com/pattern-ai-labs/built-with-agentcallWrote 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/pattern-ai-labs/built-with-agentcall/meeting-standup)<a href="https://agentmods.dev/skills/pattern-ai-labs/built-with-agentcall/meeting-standup"><img src="https://agentmods.dev/badge/skills/pattern-ai-labs/built-with-agentcall/meeting-standup/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/pattern-ai-labs/built-with-agentcall/meeting-standup"><img src="https://agentmods.dev/badge/skills/pattern-ai-labs/built-with-agentcall/meeting-standup.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 | $0.00096 | $0.04221 |
| Opus 5 | $0.00048 | $0.02110 |
| Sonnet 5 | $0.00019 | $0.00844 |
| Haiku 4.5 | $0.00010 | $0.00422 |
Grade A, and why
meeting-standup 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 12d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Standup Manager — a skill that runs your team's standup, then manages the summary
This file is the rulebook for how you behave in the meeting. Read it FULLY before every run — especially in a fresh session — and act exactly as it says. The engine handles the mechanics; every judgment call (blockers, reflections, the summary, requests, when to leave) is yours, and this file is where those rules live. Don't improvise a different protocol mid-call.
For managers and team leads. This turns your AI agent into the person who runs standup. It joins the call as an audio-only bot, greets the team, goes around one at a time by name, keeps time (so a 5-person standup is ~7 minutes, not 20), and keeps a running summary with action items. When the round's done it posts the summary in the chat and stays — it takes a latecomer's update (with a raised hand), reads the summary back if someone asks, and leaves only when asked, or when everyone else has (always stopping billing). It also remembers blockers across days and follows up on them.
You are the brain — but stay OUT of the round's way (this is the important part)
The bot runs the round itself, fast and deterministically — it auto-starts the moment anyone speaks, times each turn, drops a quick filler ("Got it, thanks") between people, and never waits on you. That is deliberate: you (an AI agent) have real latency, so if you sat in the turn-by-turn loop the meeting would lag and desync. So don't drive the round. Do your thinking asynchronously and in standby.
Your two real jobs: (A) as updates stream in, quietly record blockers; (B) when the round ends,
compose and post one clean summary, then handle anything said in standby (a fix, "what's the summary?",
"you can leave"). Everything is a tiny file link: the bot appends to link/heard.jsonl; you append one
line to link/commands.jsonl. Start watching the moment you launch:
tail -n +1 -f link/heard.jsonl # each new line is an event; append your reply to link/commands.jsonl
(POSIX; on Windows see the alternatives just below.) The bot runs what you append within ~0.12s.
What ships with it
10 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.
- 12d ago First seen · 189 lines · 96 tokens per session scan A bbcdf8774ff4
meeting-standup is a skill published in the GitHub repository pattern-ai-labs/built-with-agentcall (12 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 4,221 once invoked, about $0.0005 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 2026-08-30.
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magpie-security-issue-import-from-md
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