agf-speed-drain
Skill8 starsChanged 32 days agoNo licenceView on GitHub
Use to run a full software-delivery cycle on the agf graph at speed — from a request to tasks, subtasks, ACs and risks, then implement, test, validate, hand off and listen — with each task closed in 2-3 minutes. Covers backlog creation and enrichment (decompose, gaps, check, brief), the TDD drain loop (next → RED → GREEN → check → done → commit) and the delivery gates (gate, harness, release) by epic. Use in any project with workflow-graph/graph.db when the request is 'rápido', 'o mais rápido possível', 'entrega completa', 'decompor', 'enriquecer backlog', 'drenar backlog', 'entregar na main agora', or when earlier sessions are stuck in slow gates or merge ceremony. NÃO use for L/XL tasks, store/gateway/security changes, or when the owner asked for depth/robustness (use graph-builder-leafcutter instead). Triggers — agf-speed-drain, entrega completa, entrega rápida, drenagem rápida, ciclo rápido, enriquecer backlog, decompor, speed drain.
In this repository27 other files it gives its agents.
- agf-report-lead-timeSkill
- colony-antSkill
- colony-ctoSkill
- colony-leaderSkill
- colony-reviewerSkill
- graph-analyzeSkill
- graph-backlog-generationSkill
- graph-bugsSkill
- graph-builder-leafcutterSkill
- graph-deploySkill
- graph-designSkill
- graph-docsSkill
- graph-handoffSkill
- graph-implementSkill
- graph-listeningSkill
- graph-mega-brainSkill
- graph-planSkill
- graph-platformSkill
- graph-prdSkill
- graph-qualitySkill
- graph-reviewSkill
- graph-securitySkill
- graph-testsSkill
- graph-validateSkill
- graph-woodpeckerSkill
- kanban-orchestratorSkill
- scrum-masterSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
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≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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