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debugging-workflows

Guide for debugging GitHub Agentic Workflows - analyzing logs, auditing runs, and troubleshooting issues

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安装与使用

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技能说明

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

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 safe-inputs
   - 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
Safe-Inputs Context passed to agent safe-inputs: 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 safeinputs-gh"
  • Environment variable not available

Solution: Configure safe-inputs:

safe-inputs:
  issue:
    title: ${{ github.event.issue.title }}
    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
gh aw logs Download logs for all workflows
gh aw logs <workflow> Download logs for specific workflow
gh aw logs --json Output as JSON
gh aw logs --start-date -1d Filter by date
gh aw logs --engine copilot Filter by engine
gh aw logs --parse Generate Markdown reports
Audit Commands
Command Description
gh aw audit <run-id> Audit specific run
gh aw audit <url> Audit from GitHub URL
gh aw audit <run-id> --json Output as JSON
gh aw audit <run-id> --parse Parse logs to Markdown
MCP Commands
Command Description
gh aw mcp list List workflows with MCP servers
gh aw mcp inspect <workflow> Inspect MCP configuration
Status Commands
Command Description
gh aw status Show all workflow status
gh aw compile Compile all workflows
gh aw compile <workflow> Compile specific workflow
gh aw compile --strict Compile with security checks
Workflow Execution Commands
Command Description
gh aw run <workflow> Trigger workflow manually
gh workflow run <name>.lock.yml Alternative trigger method
gh run watch <run-id> Monitor running workflow

Additional Resources

使用示例

查看来源仓库中的使用示例与配置说明。

查看来源 ↗

来源历史

收录时间
2026-01-20
索引更新时间
2026-01-28
Branch
main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

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