debugging-workflows
Guide for debugging GitHub Agentic Workflows - analyzing logs, auditing runs, and troubleshooting issues
Install
mkdir -p .claude/skills/debugging-workflows && curl -L -o skill.zip "https://mcp.directory/api/skills/download/3224" && unzip -o skill.zip -d .claude/skills/debugging-workflows && rm skill.zipInstalls to .claude/skills/debugging-workflows
About this skill
Debugging GitHub Agentic Workflows
This skill provides comprehensive guidance for debugging GitHub Agentic Workflows, including scripts to download and analyze workflow logs, audit specific runs, and understand how agentic workflows operate.
Table of Contents
- Quick Start
- Downloading Workflow Logs
- Auditing Specific Runs
- How Agentic Workflows Work
- Common Issues and Solutions
- Advanced Debugging Techniques
- Reference Commands
Quick Start
Download Logs from Recent Runs
# Download logs from the last 24 hours
gh aw logs --start-date -1d -o /tmp/workflow-logs
# Download logs for a specific workflow
gh aw logs weekly-research --start-date -1d
# Download logs with JSON output for programmatic analysis
gh aw logs --json
Audit a Specific Run
# Audit by run ID
gh aw audit 1234567890
# Audit from a GitHub Actions URL
gh aw audit https://github.com/owner/repo/actions/runs/1234567890
# Audit with JSON output
gh aw audit 1234567890 --json
Downloading Workflow Logs
The gh aw logs command downloads workflow run artifacts and logs from GitHub Actions for analysis.
Basic Usage
# Download logs for all workflows (last 10 runs)
gh aw logs
# Download logs for a specific workflow
gh aw logs <workflow-name>
# Download with custom output directory
gh aw logs -o ./my-logs
Filter Options
# Filter by date range
gh aw logs --start-date 2024-01-01 --end-date 2024-01-31
gh aw logs --start-date -1w # Last week
gh aw logs --start-date -1mo # Last month
# Filter by AI engine
gh aw logs --engine copilot
gh aw logs --engine claude
gh aw logs --engine codex
# Filter by count
gh aw logs -c 5 # Last 5 runs
# Filter by branch/tag
gh aw logs --ref main
gh aw logs --ref feature-xyz
# Filter by run ID range
gh aw logs --after-run-id 1000 --before-run-id 2000
# Filter firewall-enabled runs
gh aw logs --firewall # Only firewall-enabled
gh aw logs --no-firewall # Only non-firewall
Output Options
# Generate JSON summary
gh aw logs --json
# Parse agent logs and generate Markdown reports
gh aw logs --parse
# Generate Mermaid tool sequence graph
gh aw logs --tool-graph
# Set download timeout
gh aw logs --timeout 300 # 5 minute timeout
Downloaded Artifacts
When you run gh aw logs, the following artifacts are downloaded for each run:
| File | Description |
|---|---|
aw_info.json | Engine configuration and workflow metadata |
safe_output.jsonl | Agent's final output content (when non-empty) |
agent_output/ | Agent logs directory |
agent-stdio.log | Agent standard output/error logs |
aw.patch | Git patch of changes made during execution |
workflow-logs/ | GitHub Actions job logs (organized by job) |
summary.json | Complete metrics and run data for all runs |
Example: Analyze Recent Failures
# Download failed runs from last week
gh aw logs --start-date -1w -o /tmp/debug-logs
# Check the summary for patterns
cat /tmp/debug-logs/summary.json | jq '.runs[] | select(.conclusion == "failure")'
Auditing Specific Runs
The gh aw audit command investigates a single workflow run in detail, downloading artifacts, detecting errors, and generating a report.
Basic Usage
# Audit by numeric run ID
gh aw audit 1234567890
# Audit from GitHub Actions URL
gh aw audit https://github.com/owner/repo/actions/runs/1234567890
# Audit from job URL (extracts first failing step)
gh aw audit https://github.com/owner/repo/actions/runs/1234567890/job/9876543210
# Audit from job URL with specific step
gh aw audit https://github.com/owner/repo/actions/runs/1234567890/job/9876543210#step:7:1
Output Options
# JSON output for programmatic analysis
gh aw audit 1234567890 --json
# Custom output directory
gh aw audit 1234567890 -o ./audit-reports
# Parse agent logs and firewall logs
gh aw audit 1234567890 --parse
# Verbose output
gh aw audit 1234567890 -v
Audit Report Contents
The audit command provides:
- Error Detection: Errors and warnings from workflow logs
- MCP Tool Usage: Statistics on tool calls by the AI agent
- Missing Tools: Tools the agent tried to use but weren't available
- Execution Metrics: Duration, token usage, and cost information
- Safe Output Analysis: What GitHub operations were attempted
Example: Investigate a Failed Run
# Get detailed audit report
gh aw audit 1234567890 --json > audit.json
# Extract key information
cat audit.json | jq '{
status: .status,
conclusion: .conclusion,
errors: .errors,
missing_tools: .missing_tools,
tool_usage: .tool_usage
}'
How Agentic Workflows Work
Understanding the workflow architecture helps in debugging.
Workflow Structure
Agentic workflows use a markdown + YAML frontmatter format:
---
on:
issues:
types: [opened]
permissions:
issues: write
timeout-minutes: 10
engine: copilot
tools:
github:
mode: remote
toolsets: [default]
safe-outputs:
create-issue:
labels: [ai-generated]
---
# Workflow Title
Natural language instructions for the AI agent.
Use GitHub context like ${{ github.event.issue.number }}.
Execution Flow
1. Trigger Event (issue opened, PR created, schedule, etc.)
↓
2. Activation Job
- Validates permissions
- Processes mcp-scripts
- Sanitizes context
↓
3. AI Agent Job
- Loads MCP servers and tools
- Executes AI agent with prompt
- Agent makes tool calls
- Agent produces output
↓
4. Safe Outputs Job
- Processes agent output
- Creates GitHub resources (issues, PRs, etc.)
- Applies labels, comments
↓
5. Completion
- Workflow summary generated
- Artifacts uploaded
Key Components
| Component | Purpose | Configuration |
|---|---|---|
| Engine | AI model to use | engine: copilot, claude, codex |
| Tools | APIs available to agent | tools: section with MCP servers |
| MCP Scripts | Context passed to agent | mcp-scripts: with GitHub expressions |
| Safe-Outputs | Resources agent can create | safe-outputs: with allowed operations |
| Permissions | GitHub token permissions | permissions: block |
| Network | Allowed network access | network: with domain/ecosystem lists |
Compilation Process
# Compile workflow to GitHub Actions YAML
gh aw compile <workflow-name>
# Result: .github/workflows/<name>.md → .github/workflows/<name>.lock.yml
The .lock.yml file is the actual GitHub Actions workflow that runs.
Common Issues and Solutions
Missing Tool Errors
Symptoms:
- Error: "Tool 'github:read_issue' not found"
- Agent cannot access GitHub APIs
Solution: Add GitHub MCP server configuration:
tools:
github:
mode: remote
toolsets: [default]
Permission Errors
Symptoms:
- HTTP 403 (Forbidden) errors
- "Resource not accessible" errors
Solution: Add required permissions:
permissions:
contents: read
issues: write
pull-requests: write
Safe-Input Errors
Symptoms:
- "missing tool configuration for mcpscripts-gh"
- Environment variable not available
Solution: Configure mcp-scripts:
mcp-scripts:
issue:
script: |
return { title: process.env.ISSUE_TITLE, body: process.env.ISSUE_BODY };
env:
ISSUE_TITLE: ${{ github.event.issue.title }}
ISSUE_BODY: ${{ github.event.issue.body }}
Safe-Output Errors
Symptoms:
- Agent tries to create resources but fails
- "Safe output not enabled" errors
Solution: Enable safe-outputs:
safe-outputs:
staged: false # Set to false to actually create resources
create-issue:
labels: [ai-generated]
Network Access Errors
Symptoms:
- Firewall denials
- URLs appearing as "(redacted)"
Solution: Configure network access:
network:
allowed:
- defaults
- python # For PyPI
- node # For npm
- "api.example.com" # Custom domains
Timeout Errors
Symptoms:
- Workflow exceeds time limit
- Agent loops or hangs
Solution: Increase timeout or optimize prompt:
timeout-minutes: 30 # Increase from default
Advanced Debugging Techniques
Polling In-Progress Runs
When a run is still executing:
# Poll until completion
while true; do
output=$(gh aw audit <run-id> --json 2>&1)
if echo "$output" | grep -q '"status":.*"\(completed\|failure\|cancelled\)"'; then
echo "$output"
break
fi
echo "⏳ Run still in progress. Waiting 45 seconds..."
sleep 45
done
Inspecting MCP Configuration
# Inspect MCP servers for a workflow
gh aw mcp inspect <workflow-name>
# List all workflows with MCP servers
gh aw mcp list
Checking Workflow Status
# Show status of all agentic workflows
gh aw status
Downloading Specific Artifacts
# Download only the agent log artifact
GH_REPO=owner/repo gh run download <run-id> -n agent-stdio.log
Inspecting Job Logs
# View specific job logs
gh run view <run-id>
gh run view --job <job-id> --log
Analyzing Firewall Logs
# Parse firewall logs for network issues
gh aw logs --parse
# Check firewall-enabled runs
gh aw logs --firewall
Debug Mode Compilation
# Compile with verbose output
gh aw compile --verbose
# Compile with strict security checks
gh aw compile --strict
# Run security scanners
gh aw compile --actionlint --zizmor --poutine
Reference Commands
Log Analysis Commands
| Command | Description |
|---|---|
Content truncated.
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