Turn a code pattern fixed in a pull request into a custom Go linter, a tool that checks code without running it. Covers a focused detection rule, tests, and registration in the linter runner.
Rewrite long prompts into shorter, clearer instructions for language models. Preserve essential requirements while removing repetition, defining scope, and making output formats and success criteria explicit to reduce ambiguity and unnecessary tokens.
Resolve merge conflicts in generated workflow lock files by rebuilding them from merged Markdown sources. The skill checks for leftover conflict markers, stages regenerated files, and verifies that unresolved paths and whitespace errors are cleared.
Review GitHub agentic workflows, automated workflows guided by AI agents, for security and correctness. Compile changes, inspect permissions and safeguards, and use available run logs to identify supported improvements to cost and execution time.
Configure Skillz in Docker to expose SKILL.md instructions, resources, and helper scripts as tools for MCP clients, applications that connect to tool servers. Covers skill folder layouts, ZIP packaging, environment variables, and workflow integration.
Generate comprehensive pytest tests - use when generating tests, creating test suites, or testing Python code
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A minimal skill example - use when learning the skill format
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Generate conventional commit messages - use when creating commits, writing commit messages, or asking for git commit help
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Team code quality checklist - use for checking Python code quality, bugs, security issues, and best practices
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Manages stacked PRs and splits multi-part work into reviewable branches with gh-stack. Use for stack creation, viewing, edits, push, submit, sync, rebase, merge, or checkout; when asked to split or isolate work for review; whenever a user mentions a stack, branch layers, dependent PRs, or gh stack; or when a stack is checked out.
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Comprehensive guidance for building web apps with opinionated defaults for tech stack, design system, and code standards. Use when user wants to create a new web application, dashboard, or interactive interface. Provides tech choices, styling guidance, project structure, and design philosophy to get users up and running quickly with a fully functional, beautiful web app.
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Analyze C++ build performance using vcperf.exe and ETL traces. Use this skill when the user wants to profile a build, understand compile bottlenecks, identify expensive headers or templates, generate JSON analysis reports, or interpret vcperf output. Covers tracing workflows, the /jsonAnalysis flag, reading the resulting JSON schema, and actionable remediation strategies for each bottleneck category.
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Route gh-aw design, creation, diagnosis, patching, active debugging, and upgrade requests to the right strategies.
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Configure or diagnose file and directory access, mounts, and host ACLs for AWF sandboxes.
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Debug GitHub Actions workflows by downloading logs, analyzing summaries, and understanding how agentic workflows and the AWF firewall work together.
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Prepare an open pull request for merge from a GitHub Copilot cloud agent. Drives Reviews, local validation, and Mergeable to a ready state. Does not merge, and cannot trigger CI.
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Practical Python scripts for debugging awf - parse logs, diagnose issues, inspect containers, test domains
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Diagnose an AWF (Agentic Workflow Firewall) failure from an error, workflow run URL, or symptom. Covers auth (api-proxy, enterprise/BYOK Copilot, OIDC, mcpg), ARC/DinD and self-hosted runners, alternative runtimes (gVisor/Kata/chroot), Squid/DNS/egress denials, CI and gh-aw safe-output failures, and suspected security regressions. Routes to the canonical diagnosis registry in docs/diagnostics.
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Decide and implement how to support a new LLM provider or agent engine in AWF - either as a proxied provider (api-proxy adapter) or a direct-API engine (domain allowlist only), e.g. Cursor, Aider, or any tool that calls its own endpoint.
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Route gh-aw design, creation, diagnosis, patching, active debugging, and upgrade requests to the right strategies.
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Debug the AWF firewall by inspecting Docker containers (awf-squid, awf-agent), analyzing Squid access logs, checking iptables rules, and troubleshooting blocked domains or network issues.
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Regenerate and post-process all agentic workflows. Use when gh-aw is updated, workflow .md files change, or when asked to recompile/regenerate workflows.
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Use the AWF (Agentic Workflow Firewall) to run commands with network isolation and domain whitelisting. Provides L7 HTTP/HTTPS egress control for AI agents.
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Keep dependencies up-to-date. Discovers outdated deps via dependabot alerts/PRs, creates one PR per ecosystem, iterates until CI is green, then assigns for review.
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