Comprehensive documentation and best practices for building Terraform providers with terraform-plugin-framework (v1.17.0). Covers providers, resources, schemas, types, validators, testing, and common pitfalls.

Decision-Linked Development (DLD) — a workflow for recording, linking, and maintaining development decisions alongside code. Skills for planning, recording, implementing, auditing, and documenting decisions via @decision annotations.

Meta-skill: how to pass skills/context to Claude sub-agents that start with fresh context, with documented SDK gotchas.

Production-grade dlib face_recognition toolkit: piecewise confidence formula, enrollment quality diagnostics, and producer-side persistence for flicker suppression.

Standards and workflows for building secure, well-structured Terraform modules, including planning gates, validation steps, and implementation guidance.

Database architecture skills, docs, and rules for high-demand multi-tenant commerce platforms (PostgreSQL source of truth, Neo4j as derived GraphRAG projection, transactional outbox, RLS-based tenant isolation). Includes live schema introspection workflow via Postgres MCP.

Spec-driven workflow covering requirement gathering, spec authoring, implementation review, and verification — with skills, rules, and evaluation scenarios.

Skills and rules for the NanoClaw host agent (Claude Code on Mac). Tile promotion, container management, staging checks, repo chain safety, and public sync.

Teaches coding agents how to build TUIs with TamboUI correctly: API-level selection, render-thread discipline, display-width safety, CSS-aware element authoring, and JFR conventions.

Configures database INSERT triggers that offload document chunking and embedding to Edge Functions.

Tessl CLI MCP tool usage guidelines

Tessl CLI MCP tool usage guidelines

Gemini Enterprise A2A configuration and rules.

Closing the intent-to-code chasm - specification-driven development with BDD verification chain

Reference tile for Themis, a Node.js and TypeScript unit test framework designed for AI coding agents. Covers unit-test authoring, Jest/Vitest migration, agent-readable failure output with repair hints, and first-class integrations for Claude Code, Cursor, and generic agents.

Hygiene patterns for any OpenCV + dlib vision pipeline: camera index probing + macOS init quirks, warmup that verifies real frames, frame-skip policy for expensive inference.

Quickstart example: Express.js API coding standards (rules)

Build terminal chat UIs with TUI4J - Elm Architecture chat client for AI agent demos with Spring Boot integration

Evidence-first pull request review with independent critique, selective challenger review, and human handoff.

Discover and apply best practice skills automatically. Gap analysis scans the codebase, skill-search fills gaps from the registry, skill-classifier separates proactive from reactive skills, quality-standards generates CLAUDE.md guidance, self-review compares code against checklists, and verification-strategy sets up test/lint/typecheck feedback loops.