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/bytesofbree/skills-lab/skill-debriefnpx skills add bytesofbree/skills-lab --skill skill-debriefgit clone --depth 1 https://github.com/bytesofbree/skills-labWrote 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/bytesofbree/skills-lab/skill-debrief)<a href="https://agentmods.dev/skills/bytesofbree/skills-lab/skill-debrief"><img src="https://agentmods.dev/badge/skills/bytesofbree/skills-lab/skill-debrief.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 | $0.00190 | $0.02544 |
| Opus 5 | $0.00095 | $0.01272 |
| Sonnet 5 | $0.00038 | $0.00509 |
| Haiku 4.5 | $0.00019 | $0.00254 |
Grade A, and why
skill-debrief 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Debrief
What this is
Skills are living documents. Over a working session you correct Claude, explain things twice, and say preferences out loud — and almost all of that context evaporates the moment the chat closes. This skill is the debrief: run it when you're done, and it turns the friction from the session you just had into precise updates to the skills you actually used, so the same corrections don't come back next time.
It is deliberately an end-of-session, on-demand ritual. Running this kind of analysis mid-conversation is disruptive and burns budget on work that isn't the task at hand. Waiting until the end means the full arc of the session is available to learn from, and the edits land in one reviewed batch instead of trickling in while you're trying to get something done.
The mindset (read this first — it governs everything below)
- Evidence over vibes. Every proposed edit must trace back to something that actually happened in this conversation. If you can't point to the moment, don't propose the change.
- Surgical, not sweeping. You are making small, targeted edits to lines that earned them — never rewriting a skill wholesale. A skill the user has tuned over months encodes taste you can't see; large "improvements" quietly destroy it. When in doubt, change less.
- Only touch what needs it. Most skills used in a session need no changes. Silence is a valid, common outcome. Do not invent work to look useful.
- The user has the final say. Default behavior is to show the diff and wait for approval before writing anything. This is a feature, not friction — especially for creative and voice-driven skills, where the user may be choosing imperfection on purpose.
Workflow
Work through these five steps in order. Steps 1–3 are analysis (cheap, do them fully). Step 4 is where anything gets written, and only with approval.
Step 1 — Scan the session
You already have this conversation in your context, so start by reflecting over it directly rather than parsing files. Walk the session start to finish and pull out the raw material:
What ships with it
1 file 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 · 198 lines · 190 tokens per session scan A a50c38dfeab1
skill-debrief is a skill published in the GitHub repository bytesofbree/skills-lab (6 stars, last pushed 1mo ago), licensed MIT. It adds 190 tokens to every session and 2,544 once invoked, about $0.0010 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.
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