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 escoffier-labs/skillet --skill misegit clone --depth 1 https://github.com/escoffier-labs/skilletWrote 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/escoffier-labs/skillet/mise)<a href="https://agentmods.dev/skills/escoffier-labs/skillet/mise"><img src="https://agentmods.dev/badge/skills/escoffier-labs/skillet/mise/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/escoffier-labs/skillet/mise"><img src="https://agentmods.dev/badge/skills/escoffier-labs/skillet/mise.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 | $0.00079 | $0.01115 |
| Opus 5 | $0.00039 | $0.00558 |
| Sonnet 5 | $0.00016 | $0.00223 |
| Haiku 4.5 | $0.00008 | $0.00112 |
Grade A, and why
mise 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 10d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mise
Mise en place for building: everything designed and in its place before you cook. It turns an idea into a design someone approved, not the first plan that sounded right in the moment. The deliverable is a written spec a separate session could implement without re-deciding anything load-bearing.
No implementation skill, no code, no scaffolding until a design is on the table and the user has said yes to it. This holds for every task, including the ones that look too small to bother with. "Too simple to design" is exactly where an unexamined assumption costs the most, because nobody slowed down to check it. The design can be three sentences for a three-sentence change, but it gets presented and approved.
What this owns, what it borrows
This skill owns the parts that turn an understood problem into a buildable design: generating real alternatives, recommending one, and shaping the choice into a spec. It does not re-invent interrogation. Pinning each load-bearing decision to an honest basis is pressure-test's job. Pull pressure-test in when the decisions are genuinely contested, when the problem is fuzzy, or when the user hands off and goes AFK. Once a decision is pinned there, take it as settled here, do not relitigate it.
The split in one line: pressure-test closes the decisions, mise shapes them into a design and a spec.
Steps
- Read the context first. Files, docs, recent commits, the surrounding code. Never spend a question on something the repo already answers.
- Scope before designing. If the request is really several independent subsystems, say so and decompose it before going deep. Run the first piece through the full flow; each piece earns its own spec later. Don't refine the details of something that needs splitting first.
- Understand the idea. One question at a time: purpose, constraints, success criteria. Prefer multiple choice over open-ended, it is easier to answer and sharper to act on. When a choice is genuinely visual (layouts, diagrams, side-by-side options), use the harness's question previews rather than describing it in a wall of prose.
- Propose 2-3 approaches. Each with its trade-offs. Lead with your recommendation and the reason for it. Never present a single approach as the only option; if you can only think of one, you have not looked hard enough.
- Present the design, scaled to its complexity. A few sentences when it is straightforward, more when it is nuanced. Confirm each section before moving to the next. Cover architecture, the pieces and their boundaries, data flow, failure handling, and how it gets tested. Design for isolation: small units, one clear purpose each, testable on their own. A file that wants to grow large is usually doing too much.
- Write the spec to
docs/specs/YYYY-MM-DD-<topic>.mdand commit it. - Self-review the spec with fresh eyes: placeholders or TBDs, sections that contradict each other, scope that should be decomposed, requirements that read two ways. Fix inline, no second pass needed.
- User reviews the written spec. Ask them to read it and wait. If they want changes, make them and re-run the self-review.
- Hand off to recipe. That is the only skill you invoke next - not a build skill, not fire, not the code itself.
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.
- 10d ago First seen · 51 lines · 79 tokens per session scan A 1536acce340f
mise is a skill published in the GitHub repository escoffier-labs/skillet (4 stars, last pushed 9d ago), licensed MIT. It adds 79 tokens to every session and 1,115 once invoked, about $0.0004 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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