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Analyze runtime and adapter logs to identify the first decisive failure signal and classify it correctly.
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Prepare, publish, verify, and record AIDD Python package releases through this repository's release/v<version> branch and GitHub Release published-event flow; use when cutting a new prerelease or release, running release dry-runs, checking PyPI/pipx/uv tool evidence, or performing post-release version-bump follow-up.
Run or prepare a manual full-flow live end-to-end scenario against a public GitHub repository with repository pinning, authored task selection, execution evidence capture, and manual post-run quality reporting.
Run harness and eval scenarios for ai_driven_dev_v2, validate document-first stage outputs, preserve runtime logs, analyze failures, and produce durable audit artifacts for deterministic and manual-live lanes.
Select, split, create, promote, and close roadmap tasks while keeping `roadmap.md` and `backlog.md` synchronized.
Map a task to the right AIDD docs, modules, checks, and scenario assets before making changes.
Make a safe change to a stage or document contract by updating contracts, validators, prompts, and scenarios together.
| name | runtime-log-triage |
| description | Analyze runtime and adapter logs to identify the first decisive failure signal and classify it correctly. |
runtime.log, events.jsonl, and validator-report.md.log-analysis.md that names the first cause, not just the final symptom.Return the likely failure class and the evidence chain that supports it.