treesitter-chunker

Generic BAML patterns for type-safe LLM prompting. Covers schema design, DTO generation, client wrappers, and cross-language codegen. Framework-agnostic.

Browser automation for documentation discovery. Use when curl fails on JS-rendered sites, when detecting available browser tools, or when configuring browser-based documentation collection.

C4 architectural modeling for documenting software architecture. Use when creating architecture diagrams, planning new systems, communicating with stakeholders, or conducting architecture reviews.

Debug and analyze web applications using Chrome DevTools MCP. Use for console log inspection, network request monitoring, performance analysis, and debugging authenticated sessions. For basic browser automation (screenshots, form filling), use browser-discovery skill instead.

Patterns and techniques for analyzing brownfield codebases. Use when onboarding to unfamiliar code, preparing for refactoring, conducting architecture reviews, or identifying technical debt.

Detect new imports in modified files and auto-install missing dependencies. Works with npm, uv, pip, cargo, go mod, and other package managers. Triggers after code implementation to keep manifests in sync.

Navigate hierarchical ai-docs indexes to find documentation. Check local docs FIRST for speed and curated context before web searching. Covers Claude Code, BAML, MCP, and other tracked libraries.

Retrieve documentation context from local ai-docs. Check here first when implementing features, debugging errors, or needing library information. Fall back to web search if topic not found locally.

Knowledge of documentation platforms and fetching strategies. Use when adding new documentation sources, determining fetch strategy for a docs site, detecting doc frameworks, or configuring the docs registry.

Detect project stack from package manifests (package.json, pyproject.toml, go.mod, Cargo.toml, pubspec.yaml, CMakeLists.txt). Auto-identify frameworks, test tools, and build systems for onboarding.

Fetch current model names from AI providers (Anthropic, OpenAI, Gemini, Ollama), classify them into tiers (fast/default/heavy), and detect new models. Use when needing up-to-date model IDs for API calls or when other skills reference model names.

Orchestrate tasks across multiple AI providers (Claude, OpenAI, Gemini, Cursor, OpenCode, Ollama). Use when delegating tasks to specialized providers, routing based on capabilities, or implementing fallback strategies.

Invoke external AI CLIs via native Task agents (Claude, Codex, Gemini, Cursor). Primary mode for multi-provider orchestration with fork-terminal fallback for auth.

Skills for orchestrating tasks across multiple AI providers and execution environments. Parent skill category containing native-invoke and related delegation patterns.

Update repository documentation after code implementation. Maintains README, CHANGELOG, docs/ folder, and inline docstrings based on changes made. Triggered by lane-executor after task completion.

Detect and report drift between database schema and code data models. Works with SQLAlchemy, Django ORM, Prisma, TypeORM, and other ORMs. Generic across any project.

Detect common security vulnerabilities in code. Covers OWASP patterns, SQL injection, bare excepts, shell injection. Framework-agnostic.

Spawn an AI coding agent in a new terminal (Claude, Codex, Gemini, Cursor, OpenCode, Copilot). Defaults to Claude Code if unspecified.

Skills for spawning external processes - AI coding agents and generic CLI commands in new terminal windows. Parent skill category for agent and terminal spawning.

Spawn a new terminal window to run CLI commands (ffmpeg, curl, python, etc.). Use for non-AI command execution.

Parse specs to extract IDs, titles, and traceability metadata (repo, path, hash).

Analyze project stack and recommend skills. Auto-detects frameworks, activates generic ai-dev-kit skills, and optionally scaffolds project-specific skills in the target repo.

"Domain vocabulary and entity relationships for {project}. Ensures consistent terminology and model understanding."

"Research workflow patterns specific to {project}. Covers research agent coordination, source management, and synthesis strategies."

"Custom test patterns and fixtures for {project}. Covers E2E, integration, and specialized testing requirements."

Extract coding standards and conventions from CONTRIBUTING.md, .editorconfig, linter configs. Use for onboarding and ensuring consistent contributions.

Generic Supabase best practices for Row Level Security, realtime subscriptions, storage, and edge functions. Framework-agnostic.

Generate test file scaffolds from source analysis with language-appropriate templates.

TOON (Token-Oriented Object Notation) encoding for LLM-efficient data representation. 30-60% token savings vs JSON for structured data.

Universal patterns for tree-sitter code parsing. Covers AST visitors, query patterns, and language plugin development. Framework-agnostic.