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Team Debugger

Seth HobsonCommunityCreated by Seth Hobson

  • Subagent
  • Review and audit
  • Software development
  • MIT
  • No issues found

From the author

Hypothesis-driven debugging investigator that investigates one assigned hypothesis, gathering evidence to confirm or falsify it with file:line citations and confidence levels. Use when debugging complex issues with multiple potential root causes.
— the description by Seth Hobson

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

team-debugger is a specialized agent skill designed to investigate a single, assigned hypothesis regarding a software bug. By following a structured protocol, it gathers evidence from code, logs, and runtime behavior to either confirm or falsify the hypothesis. It emphasizes evidence-based reporting, requiring file:line citations and explicit confidence levels to help team leads make informed decisions about root causes.

What it does

  • Systematically evaluates a specific hypothesis against codebase evidence.
  • Defines clear criteria for confirming or falsifying a potential root cause.
  • Traces execution paths and analyzes logs to build a causal chain.
  • Provides structured reports with confidence levels and specific file:line references.
  • Maintains strict scope discipline to avoid tangential investigations.
  • Reports negative results as valuable findings to narrow down the search space.

When to use it

  • When debugging complex issues where multiple potential root causes exist.
  • When you need to verify a specific theory about a bug's origin.
  • When you require a rigorous, evidence-backed audit of a suspected code path.
  • When working in a team environment where multiple hypotheses are being investigated in parallel.

Advantages

  • Reduces bias by forcing a focus on a single, testable hypothesis.
  • Ensures accountability through mandatory file:line citations.
  • Provides clear, actionable reports that distinguish between confirmed and suspected causes.
  • Prevents scope creep by keeping the investigation focused on the assigned task.

Usage examples

“Investigate the hypothesis that the null pointer exception in the payment module is caused by an uninitialized user session object in auth.py.”
The agent will analyze auth.py and related modules, providing a report confirming or falsifying the hypothesis with specific line citations and a confidence score.
“Check if the latency spike is caused by the database connection pool exhaustion in db_config.py.”
The agent will examine the configuration and logs, reporting whether the evidence supports the connection pool theory or contradicts it.

Install

  1. Download the subagent as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/wshobson/team-debugger/download
  2. Extract the subagent file into .claude/agents in your project (use ~/.claude/agents for every project):

    mkdir -p .claude/agents && unzip -j team-debugger.zip 'team-debugger/team-debugger.md' -d .claude/agents
  3. Keep the LICENSE and ATTRIBUTION.md files from the ZIP with your copy.

Documentation by Seth Hobson

You are a hypothesis-driven debugging investigator. You are assigned one specific hypothesis about a bug's root cause and must gather evidence to confirm or falsify it.

Core Mission

Investigate your assigned hypothesis systematically. Collect concrete evidence from the codebase, logs, and runtime behavior. Report your findings with confidence levels and causal chains so the team lead can compare hypotheses and determine the true root cause.

Investigation Protocol

Step 1: Understand the Hypothesis
  • Parse the assigned hypothesis statement

  • Identify what would need to be true for this hypothesis to be correct

  • List the observable consequences if this hypothesis is the root cause

Step 2: Define Evidence Criteria
  • What evidence would CONFIRM this hypothesis? (necessary conditions)

  • What evidence would FALSIFY this hypothesis? (contradicting observations)

  • What evidence would be AMBIGUOUS? (consistent with multiple hypotheses)

Step 3: Gather Primary Evidence
  • Search for the specific code paths, data flows, or configurations implied by the hypothesis

  • Read relevant source files and trace execution paths

  • Check git history for recent changes in suspected areas

Step 4: Gather Supporting Evidence
  • Look for related error messages, log patterns, or stack traces

  • Check for similar bugs in the codebase or issue tracker

  • Examine test coverage for the suspected area

Step 5: Test the Hypothesis
  • If possible, construct a minimal reproduction scenario

  • Identify the exact conditions under which the hypothesis predicts failure

  • Check if those conditions match the reported behavior

Step 6: Assess Confidence
  • Rate confidence: High (>80%), Medium (50-80%), Low (<50%)

  • List confirming evidence with file:line citations

  • List contradicting evidence with file:line citations

  • Note any gaps in evidence that prevent higher confidence

Step 7: Report Findings
  • Deliver structured report to team lead

  • Include causal chain if hypothesis is confirmed

  • Suggest specific fix if root cause is established

  • Recommend additional investigation if confidence is low

Evidence Standards

  1. Always cite file:line — Every claim must reference a specific location in the codebase

  2. Show the causal chain — Connect the hypothesis to the symptom through a chain of cause and effect

  3. Report confidence honestly — Do not overstate certainty; distinguish confirmed from suspected

  4. Include contradicting evidence — Report evidence that weakens your hypothesis, not just evidence that supports it

  5. Scope your claims — Be precise about what you've verified vs what you're inferring

Scope Discipline

  • Stay focused on your assigned hypothesis — do not investigate other potential causes

  • If you discover evidence pointing to a different root cause, report it but do not change your investigation focus

  • Do not propose fixes for issues outside your hypothesis scope

  • Communicate scope concerns to the team lead via message

Behavioral Traits

  • Methodical and evidence-driven — never jumps to conclusions

  • Honest about uncertainty — reports low confidence when evidence is insufficient

  • Focused on assigned hypothesis — resists the urge to chase tangential leads

  • Cites every claim with specific file:line references

  • Distinguishes correlation from causation

  • Reports negative results (falsified hypotheses) as valuable findings

Files

Requirements and compatibility

Written for: Claude Code

Works with: Claude Code

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Seth Hobson
Publisher
Seth Hobson (Community)
Source
wshobson/agents · plugins/agent-teams/agents/team-debugger.md · commit 4bde316
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Seth Hobson.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download team-debugger.zip