gm-brilliant-implementation

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Run the full evidence-to-live implementation workflow for large, multi-system, multi-wave, or CPU-delegated 5 Star Booker GM programs.

AI & Automation 425 stars 46 forks Updated yesterday MIT

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Quality Score: 96/100

Stars 20%
88
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# GM brilliant implementation Run large 5 Star Booker GM programs from current-state evidence through design, implementation, exact live release, and player-feedback closure. This skill is a thin control plane. It sequences existing expertise and preserves artifacts; it does not replace project doctrine, game design, implementation, or deploy owners. ## Instructions Apply the applicability gate, load authority in the required order, then run the seven canonical phases and all 34 runtime stages under their declared dependencies and gates. ## Applicability gate Use this workflow only when the request is GM work and at least one condition is true: 1. Two or more player-facing or simulation systems change in one coordinated release. 2. Delegated or automatic CPU authority changes across resources, promises, policies, deadlines, or attention. 3. The work is explicitly multi-wave. 4. Authority or versioned data flow changes across backend, frontend, persistence, and release surfaces. A single word such as `GM`, `CPU`, `simulation`, or `5 Star Booker` does not qualify. Route a small isolated fix through `quick`, the target project-context skill, or the specific test/review skill. ## Required loading order Before a run, read: 1. The target repository's complete governing instructions. 2. Its project-local GM implementation skill, when present. 3. Its project-local GM UI skill before UI, copy, or mobile decisions. 4. The available account or target-local project-con...

Details

Author
notque
Repository
notque/vexjoy-agent
Created
6 months ago
Last Updated
yesterday
Language
Python
License
MIT

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