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Part of Run AI-Assisted Development Workflows End to End

Engineering Blueprint

Debug Broken Behavior With Systematic Root-Cause Investigation

0June 2026

Structured troubleshooting that traces data flow and tests hypotheses instead of guessing.

What problem does this solve?

Debugs broken things methodically. /investigate traces the data flow from input through the failing code, tests hypotheses about where the break occurred, and stops after 3 failed fix attempts to avoid infinite loops. It produces a detailed investigation report with decision logs so learnings persist.

How does it work?

  1. Describe what's broken (error message, unexpected behavior, flow that fails). 2. /investigate freezes edits to the affected module, traces data flow from entry point to the error, and writes a hypothesis. 3. It tests the hypothesis by adding logs, reading outputs, or running a reproduction. 4. If the hypothesis fails, it revises and tests again. 5. After 3 failed hypotheses, it stops to avoid loops. Output: a detailed investigation report with data flow diagram, root cause, and (if found) a fix.

Included Skills

No skills in this group

What's required to run this?

/investigateuses/freezeto restrict edits to the affected module. Learnings log viagstack-learnings-log. Investigation reports save to ~/.gstack/projects/{slug}/`. The Iron Law (no fixes without investigation) prevents fix loops by capping hypothesis tests at 3 failures per investigation.

Key Features

/investigate

Iron Law: no fixes without investigation. Traces data flow, tests hypotheses, stops after 3 failed fixes. Freezes the module under investigation.

Data Flow Tracing

Follows the data from entry point through the failing code, noting transformations and decision points.

Hypothesis Testing

Forms and tests explicit hypotheses (using logs, tests, or output inspection) rather than guessing at fixes.

Decision Logging

Persists investigation decisions so future sessions understand what was tried and why it failed.

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