Borrowing it
Nothing to install: this file belongs to hmSchuller/tiller-ai. 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/hmSchuller/tiller-ai/main/.claude/skills/cookbook/SKILL.mdgit clone --depth 1 https://github.com/hmSchuller/tiller-aiWrote 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/hmschuller/tiller-ai/cookbook)<a href="https://agentmods.dev/skills/hmschuller/tiller-ai/cookbook"><img src="https://agentmods.dev/badge/skills/hmschuller/tiller-ai/cookbook/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/hmschuller/tiller-ai/cookbook"><img src="https://agentmods.dev/badge/skills/hmschuller/tiller-ai/cookbook.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 | $0.00027 | $0.01535 |
| Opus 5.5 | $0.00011 | $0.00614 |
| Sonnet 5.5 | $0.00005 | $0.00307 |
| Haiku 4.5 | $0.00003 | $0.00153 |
Grade A, and why
cookbook 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 2mo 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cookbook — Build a best-practices cookbook for this project
Step 1: Orient
Read .tiller/tiller.json (and .tiller/local.json if it exists) to understand the current state.
If codebase-map.md exists, read it to get a structural overview.
State the current mode: "Mode: ".
If mode is simple: Do not narrate the orient step. If mode is detailed: Summarize the project stack in 2-3 sentences.
Step 2: Detect technologies
Use the Explore agent (subagent_type: "Explore", thoroughness: "very thorough") to scan the project and identify every technology, language, framework, library, and tool that is meaningfully present. The agent should:
- Inspect
package.json,pyproject.toml,Cargo.toml,go.mod,Gemfile,pom.xml,build.gradle, and similar manifest files. - Look at file extensions present in
src/,lib/,app/, and similar source directories. - Check config files:
tsconfig.json,.eslintrc,vitest.config.*,jest.config.*,babel.config.*,webpack.config.*,vite.config.*,tailwind.config.*,Dockerfile,docker-compose.*, CI workflow files in.github/workflows/etc. - Note runtime/platform dependencies (Node.js, Python, JVM, Rust, Go, etc.).
Wait for the Explore agent to complete. Compile the results into a deduplicated list of technologies, for example:
Detected technologies:
1. TypeScript
2. Node.js
3. React
4. Vitest
5. tsup
6. Commander.js
…
Show this list to the user.
Step 3: Check for existing guidelines
For each detected technology, search the codebase for existing coding or implementation guidelines:
- Look inside
docs/,documentation/,CONTRIBUTING.md,README.md,CLAUDE.md,AGENTS.md,.tiller/TILLER.md, and any*.mdfiles at the root or in common documentation paths. - Search for technology-specific config comments, inline ADRs (Architecture Decision Records), or style notes.
Build a table:
| Technology | Existing guideline found? | Source file(s) |
|---|---|---|
| TypeScript | Yes / No / Partial | tsconfig.json, … |
| … | … | … |
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.
- 2mo ago First seen · 174 lines · 27 tokens per session scan A a697fce3ce38
cookbook is a skill published in the GitHub repository hmSchuller/tiller-ai (2 stars, last pushed 8mo ago), licensed MIT. It adds 27 tokens to every session and 1,535 once invoked, about $0.0001 per session on Opus 5.5. 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.
cookbook compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| cookbookhmSchuller/tiller-ai | Skill | 2 | 8mo ago | MIT | A | 27 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |