Find the perfect capability for your agent.
Fix GitHub issues or PR review feedback in snarkVM using TDD workflow. WHEN: User says "fix issue", "fix #123", "fix pr", "fix PR feedback", "address review comments", "resolve review threads", or wants to fix a bug/feature request from GitHub issues or address reviewer requests. WHEN NOT: Doing security review (use snarkvm-review), fetching context only (use snarkvm-github), or working on non-snarkVM code.
Fetch GitHub context (PR or issue) into workspace for snarkVM development. WHEN: User says "fetch pr", "fetch issue", "get PR context", "load issue", mentions PR/issue numbers like "#123" or "PR 456", or needs GitHub context before reviewing/fixing. WHEN NOT: User already has fresh context loaded, or is asking about non-snarkVM repositories.
Security-focused PR review for snarkVM codebase. WHEN: User says "review PR", "audit PR", "security review", "check PR changes", or wants thorough analysis of PR changes for bugs/vulnerabilities. WHEN NOT: Fixing review feedback (use snarkvm-fix pr), fetching context only (use snarkvm-github), or fixing issues (use snarkvm-fix).
Generate performance review summaries from git repositories by analyzing commits, code changes, and contribution patterns over a specified time range. Use when the user needs to create work reports, performance reviews, or contribution summaries from git history.
Create a git commit following repository conventions
Use when a problem, task, or idea needs to be tracked as a GitHub issue on tikv/pd. Searches for duplicates, picks the right issue template, drafts the title and body, shows the draft for user approval, and submits via `gh issue create`.
Generate release notes for the new NNCF release.
Increment the version of NNCF in src/nncf/version.py.
Standardize GitHub Actions workflows with minimal functional changes.
Issue creation workflow for Agent Teams Lite following the issue-first enforcement system. Trigger: When creating a GitHub issue, reporting a bug, or requesting a feature.
Activate when creating new modules, refactoring class hierarchies, introducing design patterns, or making changes spanning 3+ files in the APM CLI codebase.
Use this skill when editing or creating CLI output, logging, warnings, error messages, progress indicators, or diagnostic summaries in the APM codebase. Activate whenever code touches console helpers (_rich_success, _rich_warning, _rich_error, _rich_info, _rich_echo), DiagnosticCollector, STATUS_SYMBOLS, CommandLogger, or any user-facing terminal output — even if the user doesn't mention "logging" or "UX" explicitly.
Perform structured research and turn findings into an implementation plan.
Create, evaluate, and triage GitHub issues for CausalPy. Use when filing a bug, proposing an enhancement, analyzing existing issues, or splitting large work into parent-child sub-issues.
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
Loads internal CausalPy example datasets. Use when the user needs example data or asks about available demos.
Detect and configure a conda-compatible tool, create the CausalPy environment, and run commands inside it. Use before any task that requires Python execution.
