context7-efficient
Token-efficient library documentation fetcher using Context7 MCP with 86.8% token savings through intelligent shell pipeline filtering. Fetches code examples, API references, and best practices for JavaScript,...
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Token-efficient library documentation fetcher using Context7 MCP with 86.8% token savings through intelligent shell pipeline filtering. Fetches code examples, API references, and best practices for JavaScript,...
Automated security auditing of project dependencies to identify known vulnerabilities.
Generate comprehensive OpenAPI/Swagger specifications from existing code and APIs.
Create database migrations from model changes, schema diffs, and migration best practices.
Manage Hathor wallet-lib release process. Use when initiating a release (PR from master to release branch) or bumping version (minor/patch/major). Handles PR creation with proper templates, reviewer assignment,...
Use when reviewing a GitHub PR locally - fetches PR details, sets up isolated worktree, and provides initial review summary with existing feedback
Smart git merge conflict resolution with context analysis, pattern detection, and automated resol...
Generate comprehensive pull request descriptions that help reviewers understand changes quickly a...
Use when transcribing audio/video to text with timestamps, speaker labels, and chapters. Supports YouTube URLs and local files. Produces structured markdown output.
Use when converting between caption formats (SRT, VTT, ASS, TTML, Gemini MD, etc.). Supports 30+ caption formats.
Use when translating captions/captions to another language. Supports bilingual output and context-aware translation. Default uses Claude native, Gemini API optional.
Effectively use Narwhals to write dataframe-agnostic code that works seamlessly across multiple Python dataframe libraries. Write correct type annotations for code using Narwhals.
This skill should be used when the user asks to "define a feature", "create a BaseFeature class", "track feature versions", "set up metadata store", "field-level dependencies", "FieldSpec", "FeatureDep", "run m...
Self-reflect on the current session to identify mistakes and propose improvements to .claude configuration (CLAUDE.md, hooks, skills).
Write YAML front matter for documentation pages with appropriate titles and descriptions for social cards.
Use Hypothesis for property-based testing to automatically generate comprehensive test cases, find edge cases, and write more robust tests with minimal example shrinking. Includes Polars parametric testing inte...
Use syrupy for pytest snapshot testing to ensure the immutability of computed results, manage snapshots, customize serialization, and handle complex data structures with built-in matchers and filters.
Write legal and regulatory rules as executable, type-checked code in L4, a functional programming language for computational law. Use when formalizing contracts, legislation, regulations, policies, or complianc...
Capture learnings after completing work. Use when finishing a task, fixing a bug, discovering a pattern, or learning something worth remembering for future sessions. Helps build institutional memory.
Manage AI CLI tools (Claude Code, Gemini CLI, Codex CLI). Use when user asks about AI tool versions, updates, installation, or wants to update their AI CLI tools. Detects installed tools, checks versions, and r...
Use when designing data models, database schemas, or choosing between modeling approaches. Covers dimensional modeling, star schema, data vault, entity-relationship design, and schema evolution.
Comprehensive API security guidance covering authentication methods, rate limiting, input validation, CORS, security headers, and protection against OWASP API Top 10 vulnerabilities. Use when designing API auth...
Central authority for specification-driven development. Use when working with requirements, specifications, acceptance criteria, or any spec-driven workflow. Provides navigation to specialized skills and delega...
Use when implementing observability strategy, correlating signals, or designing monitoring systems. Covers the three pillars (logs, metrics, traces) and their integration.
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.