Investigates a bug or unexpected behavior from reproduction to root cause with a panel of independent hypothesis agents, then fixes it only when the request asks for a fix. Use when invoked explicitly to debug, diagnose, or fix a reported failure.
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---
name: investigate
description: Investigates a bug or unexpected behavior from reproduction to root cause with a panel of independent hypothesis agents, then fixes it only when the request asks for a fix. Use when invoked explicitly to debug, diagnose, or fix a reported failure.
disable-model-invocation: true
---
# investigate
Investigate the reported behavior from reproduction to root cause. Fix it only when the request authorizes a change.
The task is the text given with this invocation.
---
## Authorization
Infer the terminal condition from the request:
- diagnose, explain, audit, or identify cause: investigate and report; do not edit;
- investigate and fix, debug this, resolve, or equivalent change intent: diagnose first, then implement and verify the smallest root-cause fix;
- ambiguity that would materially change behavior: finish the diagnosis, recommend a fix, and ask one focused question before editing.
Read applicable repository instructions and preserve staged, unstaged, untracked, and concurrent user work.
## Reproduce before fixing
1. State the observed behavior, expected behavior, environment, and trigger.
2. Reproduce with the smallest reliable case. Capture exact logs, state transitions, inputs, outputs, and relevant versions without exposing secrets or sensitive data.
3. If reproduction is impossible, identify the missing condition and use the strongest available trace or static evidence. Do not present speculation as a root cause.
## Adaptive hypothesis panel
Scale by uncertainty and blast radius:
- trivial: investigate directly or use 1 specialist;
- modest: 2-3 agents;
- normal: 4-7 agents;
- broad, cross-system, intermittent, security-sensitive, or high-risk: 8-12+ agents.
Choose independent lenses such as execution tracing, debugger/reproduction, data/state, recent history, concurrency, environment/operations, security, architecture, and test gaps. Orthogonality and independence matter more than reaching a count. Launch independent agents concurrently in one dispatch. Never use nested agents.
Tiers: hypothesis investigators run on your default model; the agents that try to falsify the leading hypothesis, and the root-cause synthesis, run on your strongest model. Pin the model on every agent; an unpinned agent inherits whatever the session runs on.
Require competing hypotheses. Each hypothesis must include:
- a causal mechanism and predicted observation;
- evidence for and against;
- a falsifying probe;
- confidence and affected scope.
Run the cheapest discriminating probes first. Update the ranking from observed evidence, not votes.
## Root-cause gate
Call a cause established only when it explains the reproduction, the causal path is evidenced, plausible alternatives have been falsified or bounded, and changing the cause predicts removal of the failure.
Before any authorized fix, add or identify a root-cause test that fails for the demonstrated mechanism, not merely the visible symptom. When a deterministic automated test is impractical, record a repeatable validation procedure and why.
## Fix and verify
For authorized changes:
1. Apply the smallest fix at the causal boundary.
2. Run the root-cause test and focused regression tests.
3. Check adjacent invariants suggested by the blast radius.
4. Use an independent reviewer or verifier for consequential changes; the author does not self-approve.
If evidence disproves the leading hypothesis, return to hypothesis ranking rather than patching symptoms. Do not broaden into unrelated cleanup.
Report reproduction, evidence, hypotheses considered, established root cause and confidence, fix authorization, changed files if any, and fresh verification results.