hatch3r-gh-agentic-workflows

Solid

Sets up CI/CD agentic workflows for continuous AI-powered repository automation (GitHub Actions, Azure Pipelines, GitLab CI)

AI & Automation 26 stars 4 forks Updated 1 weeks ago MIT

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Quality Score: 83/100

Stars 20%
48
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# CI/CD Agentic Workflows Integration > **Platform detection:** Check `platform` in `.hatch3r/hatch.json` to determine which CI/CD system to use. Defaults to `"github"`. This skill guides setup for AI-powered CI/CD automation in hatch3r-managed projects. The core SKILL covers GitHub Actions (the default); non-GitHub platforms load on demand from `references/`. ## Step 0 — Detect Ambiguity (P8 B1) Before any work, scan the invocation for unresolved questions in scope, intent, acceptance criteria, target environment, or irreversibility. If any are found, ask the user via the platform-native question tool per `agents/shared/user-question-protocol.md`. Do not proceed under silent assumption. Default path, not an exception. Triggers for THIS skill: CI platform (GitHub Actions vs Azure Pipelines vs GitLab CI), AI engine (copilot vs claude vs codex), permission scope (read-only vs write), trigger pattern (schedule vs PR event vs manual), and cost-budget enforcement (token cap vs unbounded). ## Fan-out Discipline (P8 B2) Fan-out scales with task size; token cost never justifies serializing independent work (`rules/hatch3r-fan-out-discipline.md` P8 B2; `agents/shared/efficiency-patterns.md`). Emit `sub_agents_spawned: { count, rationale, task_structure }` in your output. ## Progressive Disclosure (Anthropic 2026 skills spec) | Target platform | File to read | |-----------------|--------------| | GitHub Actions (default) | This file — read sections below | | Azure DevOps Pipeli...

Details

Author
hatch3r
Repository
hatch3r/hatch3r
Created
5 months ago
Last Updated
1 weeks ago
Language
TypeScript
License
MIT

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