ato-mission

ato-mission is a Multi-stage workflow orchestration skill for AI agents, published by WillNigri in the Agentic-Tool-Optimization repository on GitHub. Skillspace rates ato-mission D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Before any multi-step work with a stated goal — a feature, a bugfix spanning multiple files, a QA sweep, a doc draft + iterations, a multi-day investigation — create an ATO Mission instead of doing it via bare `ato dispatch` calls. A Mission persists the goal + the verifiable success criteria, lets the coordinator tick drive the work across days, captures every event in a structured audit trail (SQLite + markdown narrative), and integrates parallel agents' work via merge strategies. Complement to `ato-warroom` (the cross-family decision before you start) and `ato-review` (the post-code-diff review). Missions is where multi-step work LIVES; war-rooms are where decisions ABOUT it get made; reviews are where the resulting commits get vetted. Fires when: the work has more than one decision point, a verifiable end state, or runs across more than one session. Use it for any ATO development that doesn't fit in a single dispatch.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

32

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