agentleFS
bordenetbordenet/superpowers-plus/skills/engineering/reproduction-experiment-investigator/skill.md

reproduction-experiment-investigator

Skill8 starsChanged 6 months agoMITView on GitHub

Specialized investigator for testing hypotheses through reproduction attempts. Designs experiments, executes controlled tests, and reports whether a hypothesis can be confirmed or rejected. Dispatched by debug-conductor.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Document ALL differences — any could explain failure to reproduce

    line 55
  2. Distinctive:

    If significant differences exist:

    line 56
  3. Distinctive:

    If not, document the gap as a limitation

    line 58
  4. Distinctive:

    If failure disappears → strong confirmation

    line 85
  5. Distinctive:

    If failure persists → hypothesis may be wrong or incomplete

    line 86

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
skill.md

Reproduction & Experiment Investigator

Role: Test debugging hypotheses through controlled reproduction attempts. Confirm or reject with evidence. Dispatched by: debug-conductor — never invoked directly by user. Evidence type: ExperimentEvidence (see skills/_shared/evidence-schema.md)

When to Use

Dispatched by debug-conductor when a hypothesis needs testing — controlled reproduction, environment comparison, or A/B verification of a suspected root cause.

Investigation Protocol

Step 1: Receive and Refine Hypothesis

From the conductor, receive:

  • Hypothesis: "The failure is caused by [X] when [condition Y] is present"
  • Predicted outcome: "If hypothesis is correct, we expect [Z] when we [action]"
  • Environment: Where to reproduce (staging, local, isolated sandbox)

Refine into a testable experiment:

  • Define exact steps to reproduce
  • Define exact success/failure criteria (not subjective)
  • Identify minimum reproduction conditions (strip unnecessary variables)

Step 2: Environment Assessment

  1. Compare reproduction environment to production:
    • Same versions? Same config? Same data? Same load?
    • Document ALL differences — any could explain failure to reproduce
  2. If significant differences exist:
    • Can we close the gap? (deploy same version, copy config)
    • If not, document the gap as a limitation

Step 3: Execute Controlled Reproduction (3+ attempts)

For each attempt:

  1. Reset environment to clean state
  2. Apply the hypothesized condition
  3. Execute the triggering action
  4. Record: did the expected failure occur?
  5. Record: any unexpected behavior?

Minimum 3 attempts — intermittent bugs need statistical confidence.

AttemptsReproductionsConfidence
3/33High (>0.8) — hypothesis strongly supported
2/32Medium (0.5–0.8) — likely correct but intermittent
1/31Low (0.3–0.5) — possible but unreliable
0/30Very Low (<0.3) — hypothesis likely wrong OR environment mismatch

Step 4: Control Experiment

If reproduction succeeded:

  1. Remove the hypothesized condition
  2. Re-run the same triggering action
  3. If failure disappears → strong confirmation
  4. If failure persists → hypothesis may be wrong or incomplete

Step 5: Produce Evidence

{
  "hypothesis": "Event ordering bug in async pipeline under load",
  "steps": [
    { "action": "Set event processing to async mode", "result": "Config applied", "success": true },
    { "action": "Send 50 concurrent call events", "result": "Events arrived out of order in 12/50 cases", "success": true },
    { "action": "Verify call state machine diverged", "result": "3 calls in disconnected state prematurely", "success": true }
  ],
  "outcome": "reproduced",
  "reproduced": true,
  "attempts": 3,
  "successRate": 1.0,
  "environmentDiff": "Staging uses lower load (50 concurrent vs 500 in prod); reproduction rate may differ"
}

Stop Conditions

  • Hypothesis confirmed or rejected with ≥3 attempts
  • Reproduction rate established
  • Environment assessment shows unbridgeable gap (cannot reproduce here)
  • Token budget exhausted
  • Wall-clock limit (5 minutes)

Escalation Conditions

  • 0/3 reproduction despite matching environment → hypothesis may be wrong; tell conductor
  • Intermittent reproduction (<50%) → flag as timing-dependent; may need more attempts or different conditions
  • Environment mismatch prevents reproduction → flag as "cannot test here"; need production access or closer replica

Common Patterns This Investigator Detects

PatternEvidence Shape
Deterministic bug3/3 reproduction, 0/3 without condition → confirmed
Load-dependent bugReproduces only above certain concurrency threshold
Environment-specificReproduces in prod-like environment but not staging → config/infra difference
Intermittent / race condition1–2/3 reproduction → timing-dependent
Hypothesis disproven0/3 reproduction even with condition → reject hypothesis

Failure Modes

ModeSymptomRecovery
Incomplete isolationTest affected by shared stateReset environment between experiments
False confirmationCoincidental success in reproductionRun multiple trials
Wrong variableTesting irrelevant hypothesisVerify hypothesis matches symptoms

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.