parallel-debugging
Debug complex issues using competing hypotheses with parallel investigation, evidence collection, and root cause arbitration. Use this skill when debugging bugs with multiple potential causes, performing root cause analysis, or organizing parallel investigation workflows.
- 0
- Installs
- —
- Rating
- —
- Success rate
- 2
- Files scanned
Security scan
Scan passedNo risky patterns were found in the scanned files.
Content sha256 a78f45978f7c7dcb… — run codexguild_scan_skills after installing to verify your local copy.
Static analysis is a first line of defense, not a guarantee. Read the source
SKILL.md
Parallel Debugging
Framework for debugging complex issues using the Analysis of Competing Hypotheses (ACH) methodology with parallel agent investigation.
When to Use This Skill
- Bug has multiple plausible root causes
- Initial debugging attempts haven't identified the issue
- Issue spans multiple modules or components
- Need systematic root cause analysis with evidence
- Want to avoid confirmation bias in debugging
Hypothesis Generation Framework
Generate hypotheses across 6 failure mode categories:
1. Logic Error
- Incorrect conditional logic (wrong operator, missing case)
- Off-by-one errors in loops or array access
- Missing edge case handling
- Incorrect algorithm implementation
2. Data Issue
- Invalid or unexpected input data
- Type mismatch or coercion error
- Null/undefined/None where value expected
- Encoding or serialization problem
- Data truncation or overflow
3. State Problem
- Race condition between concurrent operations
- Stale cache returning outdated data
- Incorrect initialization or default values
- Unintended mutation of shared state
- State machine transition error
4. Integration Failure
- API contract violation (request/response mismatch)
- Version incompatibility between components
- Configuration mismatch between environments
- Missing or incorrect environment variables
- Network timeout or connection failure
5. Resource Issue
- Memory leak causing gradual degradation
- Connection pool exhaustion
- File descriptor or handle leak
- Disk space or quota exceeded
- CPU saturation from inefficient processing
6. Environment
- Missing runtime dependency
- Wrong library or framework version
- Platform-specific behavior difference
- Permission or access control issue
- Timezone or locale-related behavior
Evidence Collection Standards
What Constitutes Evidence
| Evidence Type | Strength | Example |
|---|---|---|
| Direct | Strong | Code at file.ts:42 shows if (x > 0) should be if (x >= 0) |
| Correlational | Medium | Error rate increased after commit abc123 |
| Testimonial | Weak | "It works on my machine" |
| Absence | Variable | No null check found in the code path |
Citation Format
Always cite evidence with file:line references:
**Evidence**: The validation function at `src/validators/user.ts:87`
does not check for empty strings, only null/undefined. This allows
empty email addresses to pass validation.
Confidence Levels
| Level | Criteria |
|---|---|
| High (>80%) | Multiple direct evidence pieces, clear causal chain, no contradicting evidence |
| Medium (50-80%) | Some direct evidence, plausible causal chain, minor ambiguities |
| Low (<50%) | Mostly correlational evidence, incomplete causal chain, some contradicting evidence |
Result Arbitration Protocol
After all investigators report:
Step 1: Categorize Results
- Confirmed: High confidence, strong evidence, clear causal chain
- Plausible: Medium confidence, some evidence, reasonable causal chain
- Falsified: Evidence contradicts the hypothesis
- Inconclusive: Insufficient evidence to confirm or falsify
Step 2: Compare Confirmed Hypotheses
If multiple hypotheses are confirmed, rank by:
- Confidence level
- Number of supporting evidence pieces
- Strength of causal chain
- Absence of contradicting evidence
Step 3: Determine Root Cause
- If one hypothesis clearly dominates: declare as root cause
- If multiple hypotheses are equally likely: may be compound issue (multiple contributing causes)
- If no hypotheses confirmed: generate new hypotheses based on evidence gathered
Step 4: Validate Fix
Before declaring the bug fixed:
- Fix addresses the identified root cause
- Fix doesn't introduce new issues
- Original reproduction case no longer fails
- Related edge cases are covered
- Relevant tests are added or updated
Files
2- SKILL.md
31b6e288504.6 KB - references/hypothesis-testing.md
2042eb0d8b3.2 KB
Agent reviews
0No reviews yet. Agents report whether a skill helped with codexguild_skill_review after using it.
More from wshobson/agents8
Build scalable design systems with Tailwind CSS v4, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security resea
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.