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-diagnosenpx skills add shinpr/claude-code-workflows --skill recipe-diagnosegit 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-diagnose)<a href="https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-diagnose"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-diagnose.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 5.1 | $0.00015 | $0.02481 |
| Opus 5 | $0.00008 | $0.01241 |
| Sonnet 5 | $0.00003 | $0.00496 |
| Haiku 4.5 | $0.00002 | $0.00248 |
Grade A, and why
recipe-diagnose 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 6d 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 — 262 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: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts. Execute Skill: subagents-orchestration-guide before making workflow decisions, invoking agents, or resolving findings.
Context: Diagnosis flow to identify root cause and present solutions
Target problem: $ARGUMENTS
Orchestrator Definition
Core Identity: "I am an orchestrator."
Local authority gate: Make this recipe's workflow decisions and validate each returned result directly; delegate semantic deliverable production to the named specialist.
Execution Method:
- Investigation → performed by investigator
- Verification → performed by verifier
- Solution derivation → performed by solver
Orchestrator invokes sub-agents and passes structured JSON between them.
At each Agent invocation below, build the prompt as a mechanical extraction: copy the named source values into the exact fields, apply only the declared serialization, then invoke immediately.
Execution Gate: Each step below establishes evidence required by the next decision. Complete Steps 0-7 in order, including every required investigation and verification retry. Advance only through the current step's stated quality or coverage condition; invoke solver only after coverage is closed.
Step 0: Problem Structuring (Before investigator invocation)
0.1 Problem Type Determination
| Type | Criteria |
|---|---|
| Change Failure | Indicates some change occurred before the problem appeared |
| New Discovery | No relation to changes is indicated |
If uncertain, ask the user whether any changes were made right before the problem occurred.
0.2 Information Supplementation for Change Failures
If the following are unclear, ask with AskUserQuestion before proceeding:
- What was changed (cause change)
- What broke (affected area)
- Relationship between both (shared components, etc.)
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.
- 6d ago First seen · 262 lines · 15 tokens per session scan A 0403595da2f9
recipe-diagnose is a skill published in the GitHub repository shinpr/claude-code-workflows (679 stars, last pushed 2d ago), licensed MIT. It adds 15 tokens to every session and 2,481 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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