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investigate

Use when the user asks to diagnose a bug, find the root cause of a failing behavior, or run a controlled hypothesis-by-hypothesis investigation with experiments and evidence. Produces a diagnostic report with a recommended fix (but does not apply the fix). Do NOT trigger on "fix this bug" when the cause is obvious, or on simple error-message lookups.

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SKILL.md
Quality
Evals
Security

Investigate Issue

Overview

Diagnose the root cause of an issue autonomously. Propose candidate hypotheses, pick the most promising one, run discrete-outcome experiments, update probabilities with evidence, iterate. No user checkpoints. Final report recommends a fix; it does not apply one.

Context

Used for debugging and root cause analysis. The agent navigates the hypothesis space without HITL (human-in-the-loop) pauses. The user audits the trail through the printed Hypothesis Board and the final report.

Rules & Constraints

1. **No Production Changes**: Diagnostic edits (logging, probes, patches) must be reverted before the next step. The recommended fix is reported, NOT applied. 2. **Clean Baseline**: Worktree must be clean between experiments (verify via version-control status). 3. **Autonomous Flow**: Do NOT pause for user selection of hypotheses or approval of experiments. Pick the highest-probability untested hypothesis and proceed. 4. **Transparency**: Print the "Hypothesis Board" (probabilities + evidence) before each experiment and in the final report so the reasoning trail is auditable. 5. **Termination**: Stop when one hypothesis reaches ≥80% probability, when three consecutive experiments fail to shift probabilities, or after 5 iterations — whichever comes first. 6. **Task tracking**: Use a task management tool (e.g., todo write, todowrite) to record iteration state and steps.

Instructions

<step_by_step>

  1. Initialize
    • Create a task list covering the steps below.
    • Gather initial data: error messages, logs, relevant source files, reproduction steps.
  2. Hypotheses Generation
    • Propose 3-7 candidate root causes with initial probabilities (sum ≈ 100%) and one-line reasoning each.
    • Print the initial "Hypothesis Board".
  3. Experiment Loop (autonomous; no user checkpoints)
    • Pick the highest-probability untested hypothesis.
    • Design a discrete-outcome experiment; state what "Success" and "Failure" imply for the hypothesis.
    • Execute it (read code, run commands, inspect outputs). Keep any diagnostic edits isolated and revert them afterwards.
    • Record the outcome, adjust probabilities, append evidence to the Board.
    • Verify baseline is restored and print the updated Board.
    • Evaluate the termination condition (rule 5). If not met, repeat.
  4. Final Report
    • Print the final Hypothesis Board with the winning hypothesis highlighted.
    • Summarize each experiment: what was tested, what was observed, what it proved.
    • Recommend a concrete fix (file, line, proposed change) — do NOT apply it. </step_by_step>

Verification

[ ] 3-7 hypotheses generated with initial probabilities. [ ] Hypothesis Board printed before and after each experiment. [ ] Agent proceeded autonomously — no user approval checkpoints. [ ] Diagnostic changes reverted; baseline clean between experiments. [ ] Final report names a single root cause with evidence and recommends a fix without applying it.
Repository
korchasa/flowai-plugins
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