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name: bug-interview description: Analyze and review bug reports to capture repro, evidence, and the next smallest diagnostic step. Use when a bug report lacks clear reproduction.

bug-interview (wrapper)

Use Interview Kernel rules, state model, synthesis, and approval gate. Kernel-enforced: Question validity gate, DISCOVER vs DECIDE intent switch, Decisions table, and Assumptions register + approval.

What this wrapper optimizes for

• Reliable repro (or a plan to synthesize it)
• Evidence-driven narrowing (don’t guess)
• The smallest next diagnostic experiment (speed vs certainty is a user choice)

Interaction notes

• Must use default_mode_request_user_input multiple choice (3–5 options, include a recommended default).
• In Delta mode (existing bug report/ticket), extract what’s already known first; only ask what’s missing to repro or run the next experiment.
• Avoid broad log/data dumps without a hypothesis.

User profile alignment (Jamie)

Follow ~/.codex/USER_PROFILE.md: single-threaded, explicit steps, low cognitive load. Keep one question per turn and map any free-text reply to the closest option with confirmation.

Philosophy

• Bugs are solved by reliable repro + smallest next experiment.

Anti-patterns to avoid

• Jumping to fixes before confirming repro or scope.
• Treating assumptions as facts without explicit approval.
• Asking for broad logs/data dumps without a targeted hypothesis.

Variation

• Tailor prompts to the suspected layer (client/server/DB) and evidence quality.
• Avoid repeating identical option sets; vary the next-step tradeoff based on context.

Default mode + intent

• Mode: standard
• Intent: start DISCOVER, switch to DECIDE when choosing what to try next

Scope and triggers

• Bug report lacks clear reproduction steps.
• Need to narrow suspected layer quickly.
• Need a focused debug plan before touching code.

Constraints / Safety

• Redact secrets/PII by default.
• Do not request broad data dumps without a hypothesis.
• Do not proceed without a minimal repro or a clear plan to synthesize one.

Bug spine (10 prompts)

1. Expected vs actual

• One sentence each.

2. Severity / impact

• blocker / high / medium / low + workaround yes/no.

3. Repro steps (single concrete path)

• Minimal steps to reproduce (as few as possible).

4. Frequency

• always / often / rare / only once.

5. Environment

• OS + app version + runtime/browser + network context (pick the 1–2 that matter most).

6. Evidence available

• stack trace / logs / screenshot / error code / none.

7. Regression window

• Did this ever work? If yes, when did it last work (approx)?

8. Recent changes

• code / deps / config / data / environment.

9. Minimal repro artifact

• provide one minimal repro input (file, payload, request, dataset) OR synthesize one.

10. Next diagnostic step (DECIDE)

• Fastest experiment vs highest-signal experiment vs add instrumentation first.

Bug synthesis add-on (append after Kernel synthesis)

## Triage Addendum
- Repro status: confirmed / unconfirmed
- Suspected layer: client / server / DB / network / dependency / config
- Top hypotheses (1–3):
- Next diagnostic step (smallest experiment):
- Instrumentation needed (if any):
- Rollback/mitigation options:

Required inputs

• User request details and any relevant files/links.

Deliverables

• Kernel synthesis + Triage Addendum.
• Include schema_version: 1 if outputs are contract-bound.

Validation

• Fail fast and report missing inputs before proceeding.

Examples

• "I have a crash report but no repro steps—help me find the next diagnostic step."
• "This bug only happens in prod; guide me to the smallest high-signal experiment."

References

• references/contract.yaml (output contract)
• references/evals.yaml (quality checks)

Remember

The agent is capable of extraordinary work in this domain. These guidelines unlock that potential—they don't constrain it. Use judgment, adapt to context, and push boundaries when appropriate.

Procedure

1. (Optional) Delta scan: extract what’s already known from the bug report/ticket.
2. Execute the kernel interview loop using the Bug spine.
3. Synthesize outputs + approval gate.
4. Handoff to debugging/implementation using the approved triage plan.

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Philosophy and tradeoffs

• Use this skill when consistent decision-making matters more than one-off execution because project context should drive the approach.
• Principle and mindset: prioritize tradeoffs and constraints over rigid checklists; understand why each step exists.
• Ask this to keep outcomes robust: Why is this the right default, and what could change this outcome?
• How do we adapt if constraints shift?
• What evidence is needed before choosing one path over another?

Anti-patterns and caveats

• Avoid applying this playbook generically without checking repository-specific context.
• NEVER skip required validation gates when behavior changes.
• DO NOT use this skill as a rigid replacement for engineering judgment.
• DON'T ignore warnings or assume one pattern fits all repos.
• Common pitfall: treating anti-patterns as optional.
• Incorrect assumptions here can lead to fragile guidance.
• Warning: wrong sequencing can create avoidable regressions.

Variation and adaptation

• Vary the workflow by team size, risk, and deployment target.
• Use different strategies for small, medium, and large changes.
• Adapt recommendations to the specific environment and avoid repetitive templates.
• Avoid generic or cookie-cutter responses; craft context-specific alternatives.
• Keep outputs diverse and not repetitive.
• Converge on a custom path only after evidence review.
• Different constraints should produce different, non-generic recommendations.

Empowering execution style

• Be capable of exploring multiple options and enabling the team to make safe decisions.
• Unlock confidence by explaining options and tradeoffs clearly.
• Feel free to be creative while staying rigorous and precise.
• Push boundaries with practical alternatives when simple recipes fail.
• Enable outcomes-oriented problem solving.

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Decision feedback protocol (required):

• If post-run feedback capture is enabled for this runtime, emit a non-blocking post_run_feedback event via request_user_input after result delivery.
• Capture: decision (accepted|partial|rejected|deferred), outcome (good|neutral|bad|unknown), and confidence (high|medium|low).
• Persist with: python3 utilities/skill-creator/scripts/record_skill_feedback.py --skill-path <path/to/SKILL.md> --decision <...> --outcome <...> --confidence <...> --notes "...".
• The recorder tags subject (for example ui, code_review, backend, security) for cross-domain quality analytics.

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