GitHub PR lifecycle: branch, commit, open, CI, merge.
日本語の概要は準備中です。原文の説明を表示しています。
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GitHub PR lifecycle: branch, commit, open, CI, merge.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-repo git operations — init, reset, status, branch management, refresh (rebase), stacked rebase. JSON output for agent consumption.
日本語の概要は準備中です。原文の説明を表示しています。
Set up Claude Code git safety guardrails that block dangerous git commands before execution. Use when the user asks to prevent git push, hard reset, git clean, destructive checkout/restore, or branch deletion from Claude Code hooks.
日本語の概要は準備中です。原文の説明を表示しています。
Risk-tiered code review (Blocker / High / Medium / Low). Use when the user runs /review or wants the current branch or diff reviewed.
日本語の概要は準備中です。原文の説明を表示しています。
GitHub MCP Server integration for repository operations, pull requests, issues, and GitHub Actions. Triggers on: github mcp, github operations, pull request, issue, repository, github actions, commit, branch, merge.
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Complete guide for code coverage analysis. Use when you need to analyze code coverage, generate coverage reports, or configure CI/CD coverage checks. Covers Coverlet configuration, report generation, metric interpretation, and cyclomatic complexity integration. Includes Fine Code Coverage, VS Code built-in tools, and best practices. Keywords: code coverage, coverage analysis, coverage report, Coverlet, Fine Code Coverage, dotnet-coverage, ReportGenerator, line coverage, branch coverage, cyclomatic complexity, runsettings, cobertura
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Manages .NET release lifecycle. NBGV versioning, SemVer, changelogs, pre-release, branching.
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Apply DESIGN, canon, and modules to every page in the inventory, producing a deployable static HTML site. Three render branches (approved page, template-applied sibling, unique render). Per-page, incremental, idempotent, content-preserving by default.
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[BETA] Detect, review, and fix code-quality and correctness issues in an AEM as a Cloud Service project — locally, with no external services or network calls. Use whenever a user wants to check, review, assess, audit, scan, modernize, upgrade, or fix AEM Java, Sling Models, OSGi, or Maven code — for example: "check my Sling Models are implemented correctly", "review my @Inject usage", "are my Maven dependencies up to date", "scan this AEM project for issues", "modernize my Sling Models", or "fix code-quality problems". Name the files to assess, or ask it to scan the repo; it detects issues, plans, and — only when you ask — applies surgical edits on a branch or in place, then verifies with mvn compile. It recognises the intent and handles each issue type itself, reporting anything it cannot yet fix. This skill is in beta. Verify all outputs before applying them to production projects.
日本語の概要は準備中です。原文の説明を表示しています。
Git workflow, branch strategy, and commit hygiene for the portfolio.
日本語の概要は準備中です。原文の説明を表示しています。
Create, edit, fix, or explain Mermaid diagrams for relationships, decision branches, interactions, lifecycles, and data models; also use when the parent selects a diagram to materially clarify an explanation. Do not trigger for simple status, one fact, short lists, quantitative charts, or marketing slides.
日本語の概要は準備中です。原文の説明を表示しています。
Performs read-only GitHub issue or PR triage with evidence links. Use when analyzing public or repository GitHub issues/PRs without mutating labels, comments, branches, reviews, merges, or issue state.
日本語の概要は準備中です。原文の説明を表示しています。
Handle an explicit Git intent such as branch/worktree setup, commit organization, history archaeology, conflict resolution, PR preparation, or versioning; do not trigger as a process skill for every code or file change.
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Establishes git workflow guardrails including conventional commits, commit message hooks, branch naming conventions, PR templates, and code review processes. Provides hook configurations, workflow templates, and emergency bypass instructions. Use when users request "setup git hooks", "enforce commit conventions", "add PR templates", or "standardize git workflow".
日本語の概要は準備中です。原文の説明を表示しています。
Use when a Spark branch or pull request needs final diff hygiene, validation selection, commit scope, remote topology, and readiness checked before publication.
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Comprehensive CI/CD pipeline exploitation methodology covering GitHub Actions injection vectors (expression injection via PR titles and issue bodies, workflow_run event abuse, GITHUB_TOKEN over-scoping, composite action supply chain compromise), Jenkins attack paths (Groovy sandbox escapes, script console remote code execution, Java remoting deserialization, credential store dumping, shared library injection), GitLab CI exploitation (YAML anchor injection, runner registration token abuse, CI variable extraction, protected branch bypass via merge request pipelines), and Azure DevOps pipeline agent compromise with service connection theft. Includes artifact poisoning techniques across all platforms, tooling guidance for gato and jenkins-attack-framework, and maps to MITRE ATT&CK T1195.002 (Supply Chain Compromise: Compromise Software Supply Chain). Covers enumeration of pipeline configurations, privilege escalation from contributor to code execution, lateral movement through pipeline trust boundaries, and p...
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Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
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Essential Git commands and workflows for version control, branching, and collaboration.
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Git-Notes-Based knowledge graph memory system. Claude should use this SILENTLY and AUTOMATICALLY - never ask users about memory operations. Branch-aware persistent memory using git notes. Handles context, decisions, tasks, and learnings across sessions.
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Designs marketing automation workflows: email triggers, branching logic, lead scoring rules, lifecycle stage transitions. Outputs Mermaid diagrams and implementation specs for HubSpot, Klaviyo, and Mailchimp.
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Discipline an AI agent needs to work an issue/task tracker (Jira, Linear, GitHub Issues) as the shared source of truth: pull the right next item instead of inventing work, search before creating to avoid duplicates, write actionable items with checkable acceptance criteria, keep status transitions honest, and link work to items via branches/PRs/commits so progress is legible. Use when an agent picks up tracker work, files a new issue, updates status, or closes an item. NOT for authoring the PR itself (use agent-pr-authoring), roadmap-level planning and prioritization (use legible-roadmap-with-sidequests), or the mechanics of multiple agents coordinating on the same codebase (use multi-agent-coordination).
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Author a pull request an AI coding agent can actually get merged: a scoped, coherent diff; a Summary and Test Plan backed by real evidence; correct triage of required-and-blocking CI gates versus external/advisory checks (e.g. a Cloudflare Pages preview build); draft-while-WIP discipline; named fixup commits for real review findings; and a clean landing through a merge queue without force-pushing or bypassing branch protection. Use when opening, updating, triaging red CI on, or landing an agent-authored GitHub PR. NOT for this repo's internal release ceremony, actor embodiments, or contributor mirror-sync mechanics (use port-daddy-internal-dev), tracking backlog/issue lifecycle across a board (use agent-issue-tracker-workflow), or deciding what to build next / sequencing a roadmap (use legible-roadmap-with-sidequests).
日本語の概要は準備中です。原文の説明を表示しています。
Apply cognitive task analysis to expert work that depends on perceptual cues, branching judgment, and recurring monitoring loops. Use when decomposing expert capability into agent structure, simulation design, or validation interviews. NOT for ordinary step-by-step SOP capture or simple pipelines with no tacit cue layer.
日本語の概要は準備中です。原文の説明を表示しています。