mcaf-source-control — for Claude Code mcaf-source-control, dotPilot, community, for Claude Code, ide skills, agent-framework, agent-orchestration, ai-agents, ai-tools, desktop-app

v1.0.0

Über diesen Skill

Geeigneter Einsatz: Ideal for AI agents that need mcaf: source control. Lokalisierte Zusammenfassung: Run this skill's Workflow through the Ralph Loop until outcomes are acceptable. It covers agent-framework, agent-orchestration, ai-agents workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Funktionen

MCAF: Source Control
bootstrapping source-control policy
tightening branch, merge, or PR rules
documenting commit or release hygiene
dealing with secrets-in-git or repository structure issues

# Core Topics

managedcode managedcode
[11]
[1]
Updated: 4/8/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
60
Canonical Locale
en
Detected Body Locale
en

Geeigneter Einsatz: Ideal for AI agents that need mcaf: source control. Lokalisierte Zusammenfassung: Run this skill's Workflow through the Ralph Loop until outcomes are acceptable. It covers agent-framework, agent-orchestration, ai-agents workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Warum diese Fähigkeit verwenden

Empfehlung: mcaf-source-control helps agents mcaf: source control. Run this skill's Workflow through the Ralph Loop until outcomes are acceptable. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Am besten geeignet für

Geeigneter Einsatz: Ideal for AI agents that need mcaf: source control.

Handlungsfähige Anwendungsfälle for mcaf-source-control

Anwendungsfall: Applying MCAF: Source Control
Anwendungsfall: Applying bootstrapping source-control policy
Anwendungsfall: Applying tightening branch, merge, or PR rules

! Sicherheit & Einschränkungen

  • Einschraenkung: one-off git commands that do not alter repo policy
  • Einschraenkung: Repeat until outcomes are acceptable or only explicit exceptions remain.
  • Einschraenkung: For setup-only requests with no execution, return

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is mcaf-source-control?

Geeigneter Einsatz: Ideal for AI agents that need mcaf: source control. Lokalisierte Zusammenfassung: Run this skill's Workflow through the Ralph Loop until outcomes are acceptable. It covers agent-framework, agent-orchestration, ai-agents workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install mcaf-source-control?

Run the command: npx killer-skills add managedcode/dotPilot/mcaf-source-control. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for mcaf-source-control?

Key use cases include: Anwendungsfall: Applying MCAF: Source Control, Anwendungsfall: Applying bootstrapping source-control policy, Anwendungsfall: Applying tightening branch, merge, or PR rules.

Which IDEs are compatible with mcaf-source-control?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for mcaf-source-control?

Einschraenkung: one-off git commands that do not alter repo policy. Einschraenkung: Repeat until outcomes are acceptable or only explicit exceptions remain.. Einschraenkung: For setup-only requests with no execution, return.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add managedcode/dotPilot/mcaf-source-control. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use mcaf-source-control immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

mcaf-source-control

Install mcaf-source-control, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

MCAF: Source Control

Trigger On

  • bootstrapping source-control policy
  • tightening branch, merge, or PR rules
  • documenting commit or release hygiene
  • dealing with secrets-in-git or repository structure issues

Value

  • produce a concrete project delta: code, docs, config, tests, CI, or review artifact
  • reduce ambiguity through explicit planning, verification, and final validation skills
  • leave reusable project context so future tasks are faster and safer

Do Not Use For

  • CI/CD workflow design with no source-control policy change
  • one-off git commands that do not alter repo policy

Inputs

  • current branching and merge flow
  • release strategy and versioning expectations
  • secret-handling and repository-structure constraints

Quick Start

  1. Read the nearest AGENTS.md and confirm scope and constraints.
  2. Run this skill's Workflow through the Ralph Loop until outcomes are acceptable.
  3. Return the Required Result Format with concrete artifacts and verification evidence.

Workflow

  1. Agree on merge and release strategy before scaling implementation.
  2. Keep branch and PR rules explicit in-repo.
  3. Treat secrets in git history as a critical incident, not cleanup noise.
  4. Use concrete policy language, not hand-waving.

Deliver

  • clear branch and merge strategy
  • updated contribution or governance docs
  • safer repository hygiene around commits, PRs, and secrets

Validate

  • naming and merge rules are explicit
  • release/versioning implications are documented where needed
  • secret hygiene is treated as policy, not tribal knowledge

Ralph Loop

Use the Ralph Loop for every task, including docs, architecture, testing, and tooling work.

  1. Brainstorm first (mandatory):
    • analyze current state
    • define the problem, target outcome, constraints, and risks
    • generate options and think through trade-offs before committing
    • capture the recommended direction and open questions
  2. Plan second (mandatory):
    • write a detailed execution plan from the chosen direction
    • list final validation skills to run at the end, with order and reason
  3. Execute one planned step and produce a concrete delta.
  4. Review the result and capture findings with actionable next fixes.
  5. Apply fixes in small batches and rerun the relevant checks or review steps.
  6. Update the plan after each iteration.
  7. Repeat until outcomes are acceptable or only explicit exceptions remain.
  8. If a dependency is missing, bootstrap it or return status: not_applicable with explicit reason and fallback path.

Required Result Format

  • status: complete | clean | improved | configured | not_applicable | blocked
  • plan: concise plan and current iteration step
  • actions_taken: concrete changes made
  • validation_skills: final skills run, or skipped with reasons
  • verification: commands, checks, or review evidence summary
  • remaining: top unresolved items or none

For setup-only requests with no execution, return status: configured and exact next commands.

Load References

  • read references/source-control.md first
  • open references/naming-branches.md only when the task is specifically about branch naming

Example Requests

  • "Define branch naming and merge rules for this repo."
  • "Document how releases and component versions should work."
  • "Tighten our source-control policy after a secrets leak."

Verwandte Fähigkeiten

Looking for an alternative to mcaf-source-control or another community skill for your workflow? Explore these related open-source skills.

Alle anzeigen

openclaw-release-maintainer

Logo of openclaw
openclaw

Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞

333.8k
0
Künstliche Intelligenz

widget-generator

Logo of f
f

Erzeugen Sie anpassbare Widget-Plugins für das Prompts.Chat-Feed-System

149.6k
0
Künstliche Intelligenz

flags

Logo of vercel
vercel

Das React-Framework

138.4k
0
Browser

pr-review

Logo of pytorch
pytorch

Tensor und dynamische neuronale Netze in Python mit starker GPU-Beschleunigung

98.6k
0
Entwickler