ai-development-guide
Applies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend…
Investigate problem, verify findings, and derive solutions
$ npx -y skills add shinpr/claude-code-workflows --skill recipe-diagnose --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/recipe-diagnoseContext preview
The summary Claude sees to decide when to auto-load this skill.
Investigate problem, verify findings, and derive solutions
name: recipe-diagnose description: Investigate problem, verify findings, and derive solutions disable-model-invocation: true
**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
**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**:
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.
Define a semantic scope envelope from the reported problem and repository evidence by recording:
The envelope bounds relevance. Keep every relationship above active throughout investigation, including after a plausible cause appears.
Problem → scope envelope → investigator → verifier
↑ │
└── named gaps ───┘
coverage closed → design decision gate when applicable → solver → Report
material evidence unavailable → limitation/block report**Context Separation**: Pass only structured JSON output to each step. Each step starts fresh with the JSON data only.
**Agent tool invocation**:
subagent_type: investigator description: "Investigate problem" prompt: | Comprehensively collect information related to the following phenomenon. Phenomenon: [Problem reported by user verbatim] diagnosisScopeEnvelope: [Step 0 semantic scope envelope]
**Expected output**: scopeAccounting, pathMap (execution paths per symptom), failurePoints (faults found at each node), impactAnalysis per failure point, unexplored areas, investigation limitations
Review investigation output:
**Quality Check** (verify JSON output contains the following):
**If quality insufficient**: Re-run investigator specifying missing items explicitly:
prompt: | Re-investigate with focus on the following gaps: - Missing: [unsatisfied Step 2 Quality Check items, copied as written] Use these previous investigation results as context and investigate only the gaps listed above. Return one updated complete investigation JSON, retaining prior evidence that remains valid: [Previous investigation JSON]
Proceed to verifier once quality is satisfied.
**Agent tool invocation**:
subagent_type: verifier description: "Verify investigation results" prompt: Verify the following investigation results against the semantic diagnosis scope envelope. diagnosisScopeEnvelope: [Step 0 semantic scope envelope] Investigation results: [Investigation JSON output]
**Expected output**: Scope-envelope coverage, coverage check (missing paths, unchecked nodes), Devil's Advocate evaluation per failure point, failure point evaluation with checkStatus, coverage assessment and disposition
**Coverage Criteria**:
Claude Code can explore a codebase deeply. On non-trivial work, the harder problem is convergence.
Repo: shinpr/claude-code-workflows
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