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/shinpr/claude-code-workflows/recipe-designnpx skills add shinpr/claude-code-workflows --skill recipe-designgit clone --depth 1 https://github.com/shinpr/claude-code-workflowsWrote 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/shinpr/claude-code-workflows/recipe-design)<a href="https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-design"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-design.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 | $0.00019 | $0.01770 |
| Opus 5 | $0.00010 | $0.00885 |
| Sonnet 5 | $0.00004 | $0.00354 |
| Haiku 4.5 | $0.00002 | $0.00177 |
Grade A, and why
recipe-design 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explicit User Instruction: The user explicitly instructs and authorizes every subagent call named in this recipe. Execute each applicable call when its prerequisites are met.
Execute Skill: documentation-criteria before document routing or creation.
Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts.
Execute Skill: subagents-orchestration-guide before invoking agents or resolving findings.
Before the first finding disposition, read references/review-resolution.md from the loaded subagents-orchestration-guide skill.
Outcome and Ownership
Coordinate the design phase from repository evidence to an approved Design Doc. The orchestrator owns requirement convergence, Structural Scale, ADR qualification, evidence selection, and Review Resolution. Named specialists own semantic investigation and artifact authorship.
The Design Doc is always the complete implementation design for Medium/Large work. A qualifying ADR batch narrows technical choices before the Design Doc, which retains the complete flow and implementation boundary.
Requirements: $ARGUMENTS
Flow
requirement source -> codebase-analyzer -> scope/decision confirmation [Stop]
|
optional ADR batch -> batch review [Stop]
|
Design Doc -> code-verifier -> Review Resolution
|
document-reviewer -> design-sync -> approval [Stop]
Execute each dependent step after its prerequisite evidence exists. Use Review Resolution for every actionable verifier, reviewer, or design-sync finding. Wait at each [Stop] for explicit user confirmation.
At each Invoke below, build the Agent prompt as a mechanical extraction: copy the named source values into the exact fields, apply only the declared serialization, then invoke immediately.
Step 1: Select the Governing Requirement Source
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 · 141 lines · 19 tokens per session scan A 1aab1e685def
recipe-design is a skill published in the GitHub repository shinpr/claude-code-workflows (675 stars, last pushed 7d ago), licensed MIT. It adds 19 tokens to every session and 1,770 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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