Review git and gh operations in gh-aw workflows to check credential availability for each repository. Identify missing token handoffs, risky expansions of limited checkouts, and error handling needed where credentials are intentionally unavailable.
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Update the gh-aw-firewall version used by gh-aw, rebuild generated files, and review release notes and configuration schemas, which define valid settings. It guides related code and test updates while identifying follow-up work that remains.
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Define and check GitHub Copilot instructions and specialized agents using Markdown files. It explains file locations, configuration fields, tool access, path-specific rules, and workflow integration, with examples for documentation, testing, reviews, and other development tasks.
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Create GitHub Copilot coding tasks from plain-language instructions using the GitHub CLI extension. Tasks become issues that trigger code changes and pull requests for review, with commands to list tasks, inspect details, and update instructions.
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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.
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Build and troubleshoot canvas extensions displayed in the GitHub Copilot app's side panel. Follow guidance for scaffolding, implementing actions and inputs, preserving state, matching app themes, and checking behavior through canvas tools and extension logs.
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Implement and test Go codemods, automated migration routines used by gh aw fix. The guide covers targeted configuration changes, preserving comments and document content, safe repeated execution, and checks for registration and execution order.
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Add an agent execution engine to gh-aw using a shared Markdown definition where possible. The skill guides installation, authentication, configuration, and testing, with Go infrastructure changes reserved for capabilities that existing settings cannot express.
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Routes requests to design, create, update, debug, or upgrade GitHub Agentic Workflows to the appropriate instructions. It helps the agent select a workflow-specific procedure and apply any additional rules defined for the repository.
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Write JavaScript for actions/github-script@v8 in GitHub Actions. Apply consistent logging, pass outputs and environment variables to later steps, publish readable summaries, and handle errors with the action's provided utilities.
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Improve validation errors in gh-aw so users can see what went wrong, what input is expected, and how to fix it. Provides writing patterns, valid YAML examples, Go error-handling guidance, and checks for message quality.
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Format gh-aw terminal output using Go struct tags, annotations attached to data fields. Set labels and section titles, format numbers and dollar amounts, omit empty fields, and render lists of records as tables.
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Prepare an open pull request for human merging from a GitHub Copilot cloud agent. Address review threads, validate changes locally, resolve branch conflicts, and report remaining blockers, including the need for a human to rerun CI.
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Review regular expressions used to detect errors in agent engines. Check for empty matches, test patterns against real logs, and add safeguards against repeated matches that can cause JavaScript loops to hang.
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Handle pull request review feedback by collecting comments, grouping requests, planning fixes, and validating changes before replying. The workflow covers team members and trusted GitHub automation, with individual replies and resolution of addressed discussion threads.
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Analyze gh-aw execution traces, which record individual processing steps, to investigate slow or failing workflows. Using local JSONL files or telemetry backends, the skill checks timing, errors, missing attributes, and trace connections to support focused improvements.
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List GitHub Actions workflows with a script that lets you choose the page size and page number. Get JSON containing the total count, workflow names, file paths, states, timestamps, and links for inspection or further processing.
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Inspect JSON files or API responses with jq and produce a compact map of keys and value types. Use the result to understand nested data before writing queries or processing the full dataset.
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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.
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Retrieve labels from a GitHub repository, filter their names by partial matches, and choose page sizes and page numbers. Results arrive as JSON, including label names, colors, descriptions, and pagination details.
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Automate browser tasks such as clicking, filling forms, and navigating tabs. Inspect page structure, console messages, and network requests, and capture screenshots or recordings to support web testing, debugging, and UI feedback.
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Design metrics that measure whether a workflow achieved its intended outcome using recorded session evidence. Choose built-in checks or custom JavaScript, retain suitable Bash evaluators, and define tests that distinguish success, failure, and missing evidence.
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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.
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Find and review pull requests created with GitHub Copilot using author searches, branch names, and Git history. Follow practical checks for changes and tests, and export request lists to CSV to track contributions.
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