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Execute an approved wish in dependency order with scoped workers, independent review, bounded repairs, and verified completion.

AI & Automation 343 stars 53 forks Updated today MIT

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Quality Score: 93/100

Stars 20%
84
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Work Read the wish and require persisted `APPROVED`, or `IN_PROGRESS` for a resume. The coordinator sets `IN_PROGRESS` before execution and owns task completion and review evidence. Documents remain the instruction source. ## Dispatch Derive ready waves from WISH.md’s Execution Strategy and per-group `depends-on`. A task DB row being `ready` does not prove its dependencies are met; the DAG lives in the document. Order the work inside a group as tracer bullets: dispatch the thinnest slice that runs end to end first, then widen it. A slice that crosses every layer proves the interfaces exist and tells the next slice what it may assume, while layers finished separately prove nothing until the last one lands. Delegate each independent group through the active runtime’s native surface, using the plan’s portable role and supported runtime configuration. Inherit the active model unless the user or an evidenced capacity diagnosis authorizes a change. If delegation is unavailable, report that limitation; do not pretend independent review occurred. Give each worker its goal, deliverables, criteria, validation, dependencies, owned files, relevant context, and stop conditions. Include task identifiers when available. Keep doing independent coordination/integration work while workers run. Parallel writers need disjoint file ownership or dedicated worktrees; otherwise sequence them. Shared-workspace workers do not change repo-level git state (`checkout`, `switch`, `reset`, `stash`...

Details

Author
automagik-dev
Repository
automagik-dev/genie
Created
1 years ago
Last Updated
today
Language
TypeScript
License
MIT

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