plan-incremental-commits
Review a mixed working tree and produce (and optionally execute) a small, logically grouped sequence of incremental git commits.
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Review a mixed working tree and produce (and optionally execute) a small, logically grouped sequence of incremental git commits.
Capture a YouTube video transcript as raw material using `ytt`, storing it in the raw/ directory with minimal metadata for later distillation.
Capture a web page as raw material (extracted text/Markdown) with metadata, storing it in the raw/ directory for later distillation.
Transform raw captured content into distilled knowledge by extracting topics (outline), summary, key points, principles, patterns, entities, and quotes, storing the result in the distilled/ directory.
Use when contributing skills back to the community. Follow git workflow: sync upstream → create branch → develop skill → test with writing-skills → commit → push → PR. One skill per PR.
Use when completing tasks or major features. Know when and how to request reviews. Provides git commit range to code-reviewer agent.
Use to validate process documentation. Apply TDD to skill writing: RED (run without skill, document failures) → GREEN (write skill) → REFACTOR (close loopholes). Test under pressure: time constraints, sunk cost...
Vercel deployment patterns and best practices. Use when deploying frontend applications, configuring edge functions, setting up preview deployments, or optimizing Next.js applications.
Google Cloud Platform architecture patterns and best practices. Use when designing, deploying, or reviewing GCP infrastructure including GKE, Cloud Run, Cloud Functions, BigQuery, and IAM.
Use when multiple independent tasks can run simultaneously. Enables efficient parallel work execution with specialized agents.
Use when finishing any task. Final checklist before marking complete. Ensures nothing forgotten, all tests pass, documentation updated.
Use when working on multiple features simultaneously. Creates isolated workspaces without branch switching, enabling parallel development.
AWS cloud architecture patterns and best practices. Use when designing, deploying, or reviewing AWS infrastructure including EC2, ECS, EKS, Lambda, RDS, S3, IAM, and VPC.
Use when decomposing complex work. Dispatch fresh subagent per task, review between tasks. Flow: Load plan → Dispatch task → Review output → Apply feedback → Mark complete → Next task. No skipping reviews, no p...
Use when setting up CI/CD pipelines. Teaches pipeline design principles and references platform-specific templates.
Use when integrating LLM APIs into applications. Covers API patterns, prompt templates, streaming, error handling, cost optimization, and provider abstraction. Apply when building chat interfaces, completion en...
Use when tests fail intermittently. Replace arbitrary timeouts with condition polling. Eliminates flaky tests caused by timing assumptions.
Use when processing code review feedback. Technical evaluation of feedback, verify before implementing. No performative agreement or gratitude.
Configuration management with Ansible. Use when automating server setup, application deployment, orchestrating multi-server tasks, or managing infrastructure configuration.
Use when implementing a multi-step plan. Execute systematically with verification checkpoints to catch errors early.
Use when ready to merge feature branch. Complete checklist before creating PR/MR. Ensures professional quality and prevents embarrassing mistakes.
Use after brainstorming, before implementation. Breaks work into discrete, actionable tasks with clear verification points.
MANDATORY setup for all projects. Automated code quality enforcement before commits. Prevents bad code from entering repository.
Use when testing frontend applications. AI-assisted browser testing with Playwright MCP. Fast, deterministic, no vision models needed.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.