Team Debugger
Seth HobsonCommunityCreated by Seth Hobson
- Subagent
- Review and audit
- Software development
- MIT
- No issues found
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
Download the subagent as a ZIP:
https://autogineer.com/agent-skills/wshobson/team-debugger/downloadExtract 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/agentsKeep 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
Always cite file:line — Every claim must reference a specific location in the codebase
Show the causal chain — Connect the hypothesis to the symptom through a chain of cause and effect
Report confidence honestly — Do not overstate certainty; distinguish confirmed from suspected
Include contradicting evidence — Report evidence that weakens your hypothesis, not just evidence that supports it
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
- ATTRIBUTION.mdAdded by AutoGineer967 B
- LICENSELicence file added by AutoGineer1.0 KiB
- team-debugger.md3.7 KiB
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 or Seth Hobson.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download team-debugger.zip