changelog
Changelog
Collaborating skills
- Git Commit: skill:
git-commit— commit the updated CHANGELOG.md with a conventional message - Create PR: skill:
create-pr— open a release PR after updating the changelog
Workflow
Step 1: Gather changes from git
# Find the last tag
git describe --tags --abbrev=0
# List commits since last tag (replace v1.2.0 with the tag found above)
git log v1.2.0..HEAD --oneline --no-merges
# See full commit messages for detail
More from mguinada/agent-skills
refactor
TDD-based code refactoring preserving behavior through tests. Use Red-Green-Refactor cycles to apply refactoring patterns one test-verified change at a time. **TRIGGERS**: 'clean up code', 'make code simpler', 'reduce complexity', 'refactor this', 'apply DRY', 'extract method', 'remove duplication'. **DISTINCT FROM**: Adding features (use /tdd) or fixing bugs. **PROACTIVE**: Auto-invoke when test-covered code has complexity (functions >50 lines, high cyclomatic complexity, duplication).
16ai-engineering
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of \"agent\", \"workflow\", \"agentic\", \"autonomous\". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.
13git-commit
Generate concise, descriptive git commit messages following best practices. Use when creating git commits from staged changes, crafting commit messages, or reviewing commit message quality. Use when the user says /commit or asks to create a git commit. **PROACTIVE ACTIVATION**: Auto-invoke when staged changes detected or user asks to commit/save work. **DETECTION**: Run git status - if staged changes exist, offer to commit. User says \"commit\", \"save\", \"done with feature\". **USE CASES**: Staged changes detected, work completed, user wants to save progress.
12tdd
Guide Test-Driven Development workflow (Red-Green-Refactor) for new features, bug fixes, and refactoring. Supports both Python (pytest) and Ruby (RSpec). Use when writing tests, implementing features, or following TDD methodology. **PROACTIVE ACTIVATION**: Auto-invoke when implementing features or fixing bugs in projects with test infrastructure. **DETECTION**: Check for tests/ directory, pytest.ini, pyproject.toml with pytest config, spec/ directory, .rspec file, or *_spec.rb files. **USE CASES**: Writing production code, fixing bugs, adding features, legacy code characterization.
11create-pr
Creates GitHub pull requests with properly formatted titles, a body matching the project's PR template, and appropriate type/scope labels. Automatically creates labels if they don't exist. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request. **PROACTIVE ACTIVATION**: Auto-invoke when a branch has commits ahead of main and the user signals the work is ready. **DETECTION**: Run git log origin/main..HEAD - if commits exist and user signals readiness, offer to open a PR. User says \"open a PR\", \"ready for review\", \"this is done\", \"let's merge\", \"submit this\". **USE CASES**: Feature or fix complete, user finished a series of commits and mentions review or merging.
11prompt-engineering
Creates system prompts, writes tool descriptions, and structures agent instructions for agentic systems. Use when the user asks to create, generate, or design prompts for AI agents, especially for tool-using agents, planning agents, or autonomous systems. **PROACTIVE ACTIVATION**: Auto-invoke when designing prompts for agents, tools, or agentic workflows in AI projects. **DETECTION**: Check for agent/tool-related code, prompt files, or user mentions of \"prompt\", \"agent\", \"LLM\". **USE CASES**: Designing system prompts, tool descriptions, agent instructions, prompt optimization, reducing hallucinations.
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