164 lines
4.0 KiB
YAML
164 lines
4.0 KiB
YAML
kind: WavePipeline
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metadata:
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name: ops-debug
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description: "Systematic debugging with hypothesis testing"
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release: true
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skills:
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- "{{ project.skill }}"
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input:
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source: cli
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example: "TestPipelineExecutor fails with nil pointer on resume"
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steps:
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- id: reproduce
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persona: debugger
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model: claude-haiku
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thread: debug
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workspace:
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mount:
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- source: ./
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target: /project
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mode: readonly
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exec:
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type: prompt
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source: |
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Reproduce and characterize the issue: {{ input }}
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1. Understand expected vs actual behavior
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2. Create minimal reproduction steps
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3. Identify relevant code paths
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4. Note environmental factors (OS, versions, config)
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output_artifacts:
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- name: reproduction
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path: .wave/output/reproduction.json
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type: json
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retry:
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policy: patient
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max_attempts: 2
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handover:
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contract:
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type: json_schema
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source: .wave/output/reproduction.json
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schema_path: .wave/contracts/debug-reproduction.schema.json
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on_failure: retry
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- id: hypothesize
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persona: debugger
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thread: debug
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dependencies: [reproduce]
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memory:
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inject_artifacts:
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- step: reproduce
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artifact: reproduction
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as: issue
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exec:
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type: prompt
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source: |
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Form hypotheses about the root cause.
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For each hypothesis:
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1. What could cause this behavior?
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2. What evidence would confirm/refute it?
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3. How to test this hypothesis?
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Rank by likelihood and ease of testing.
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output_artifacts:
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- name: hypotheses
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path: .wave/output/hypotheses.json
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type: json
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retry:
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policy: patient
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max_attempts: 2
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handover:
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contract:
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type: json_schema
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source: .wave/output/hypotheses.json
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schema_path: .wave/contracts/debug-hypotheses.schema.json
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on_failure: retry
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- id: investigate
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persona: debugger
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thread: debug
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dependencies: [hypothesize]
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memory:
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inject_artifacts:
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- step: reproduce
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artifact: reproduction
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as: issue
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- step: hypothesize
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artifact: hypotheses
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as: hypotheses
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workspace:
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mount:
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- source: ./
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target: /project
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mode: readonly
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exec:
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type: prompt
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source: |
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Test each hypothesis systematically.
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1. Start with most likely / easiest to test
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2. Use git bisect if needed to find regression
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3. Add diagnostic logging to trace execution
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4. Examine data flow and state changes
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5. Document findings for each hypothesis
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Continue until root cause is identified.
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output_artifacts:
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- name: findings
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path: .wave/output/investigation.md
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type: markdown
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handover:
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contract:
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type: non_empty_file
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source: .wave/output/investigation.md
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- id: fix
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persona: craftsman
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dependencies: [investigate]
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thread: debug
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max_visits: 3
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memory:
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inject_artifacts:
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- step: investigate
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artifact: findings
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as: root_cause
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workspace:
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mount:
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- source: ./
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target: /project
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mode: readwrite
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exec:
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type: prompt
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source: |
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Fix the root cause identified in the investigation.
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1. Implement the minimal fix
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2. Add a regression test that would have caught this
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3. Remove any diagnostic code added during debugging
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4. Verify the original reproduction no longer fails
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5. Check for similar issues elsewhere
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retry:
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policy: aggressive
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max_attempts: 3
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output_artifacts:
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- name: fix
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path: .wave/output/fix-summary.md
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type: markdown
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- id: run-tests
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type: command
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dependencies: [fix]
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script: "{{ project.contract_test_command }}"
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- id: verify-fix
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type: conditional
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dependencies: [run-tests]
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edges:
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- target: _complete
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condition: "outcome=success"
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- target: fix
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