gh-aw Workflow Diagnosis

# Download logs from the last 24 hours
gh aw logs --start-date -1d -o .github/aw/logs/recent

# 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 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

# 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 .github/aw/logs/custom

# 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

# 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

# Download failed runs from last week
gh aw logs --start-date -1w -o .github/aw/logs/debug

# Check the summary for patterns
cat .github/aw/logs/debug/summary.json | jq '.runs[] | select(.conclusion == "failure")'

# 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

# 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

# Compare existing runs, without dispatching new ones
gh aw audit 1234567890 1234567891 1234567892 --group --json

# Get detailed audit report
gh aw audit 1234567890 --json > audit.json

# Extract key information
cat audit.json | jq '{
  status: .overview.status,
  conclusion: .overview.conclusion,
  errors: .errors,
  missing_tools: .missing_tools,
  tool_usage: .tool_usage
}'

---
on:
  issues:
    types: [opened]
permissions:
  contents: read
timeout-minutes: 10
engine: copilot
tools:
  github:
    mode: remote
    toolsets: [default]
safe-outputs:
  staged: true
  create-issue:
    labels: [ai-generated]
---

# Workflow Title

Natural language instructions for the AI agent.

Use GitHub context like ${{ github.event.issue.number }}.

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

# Compile workflow to GitHub Actions YAML
gh aw compile <workflow-name>

# Result: .github/workflows/<name>.md → .github/workflows/<name>.lock.yml

tools:
  github:
    mode: remote
    toolsets: [default]

permissions:
  contents: read
safe-outputs:
  staged: true
  create-issue: {}

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-outputs:
  staged: true  # Preview safe outputs while debugging
  create-issue:
    labels: [ai-generated]