Borrowing it
Nothing to install: this file belongs to cybertronai/SutroYaro. 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/cybertronai/SutroYaro/main/.claude/skills/prepare-meeting/SKILL.mdgit clone --depth 1 https://github.com/cybertronai/SutroYaroWrote 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/cybertronai/sutroyaro/prepare-meeting)<a href="https://agentmods.dev/skills/cybertronai/sutroyaro/prepare-meeting"><img src="https://agentmods.dev/badge/skills/cybertronai/sutroyaro/prepare-meeting/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/cybertronai/sutroyaro/prepare-meeting"><img src="https://agentmods.dev/badge/skills/cybertronai/sutroyaro/prepare-meeting.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 | $0.00020 | $0.00286 |
| Opus 5 | $0.00010 | $0.00143 |
| Sonnet 5 | $0.00004 | $0.00057 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
prepare-meeting 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.
What it actually says
Prepare Meeting
Steps
-
Read the latest catch-up in
docs/catchups/for what happened this week. -
Check which experiments were run since the last meeting. Look at
research/log.jsonlanddocs/findings/for new entries. -
Compile results into a report. Create
docs/catchups/meeting-{N}-report.mdwith:- What experiments were run and their results
- Tables with actual numbers (DMC, ARD, accuracy, time)
- What changed in the codebase (new features, infrastructure)
- Open questions for discussion
- Links to findings docs and plots
-
Check for plots in
results/plots/. Reference them in the report if relevant. -
List open GitHub issues that are relevant to discuss.
-
Add the report to mkdocs.yml nav under Weekly Catch-Up.
-
Run the anti-slop skill on the report before finalizing.
Checklist
- Latest catch-up read
- New experiments identified
- Report created with tables and numbers
- Plots referenced
- Open issues listed
- Nav updated
- Anti-slop pass done
What ships with it
2 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.
- 11d ago First seen · 38 lines · 20 tokens per session scan A 463cd629974a
prepare-meeting is a skill published in the GitHub repository cybertronai/SutroYaro (16 stars, last pushed 3mo ago), licensed Unlicense. It adds 20 tokens to every session and 286 once invoked, about $0.0001 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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