4,247 artifacts
Every listing is pinned to a commit and evaluated before it goes public.
System health check (MOT) for skills, agents, hooks, and memory
Fast codebase search via WarpGrep (20x faster than grep)
Processes GCP infrastructure design and deployment workflows. Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Don't use for non-GCP cloud providers, or general Terraform coding outside the ADC context.
Fast file editing via Morph Apply API (10,500 tokens/sec, 98% accuracy)
Migration workflow - research → analyze → plan → implement → review
Research-to-implement pipeline chaining 5 MCP tools with graceful degradation
Deterministic router for math cognitive stack - maps user intent to exact CLI commands
Guide to the math cognitive stack - what tools exist and when to use each
Search Mathlib for lemmas by type signature pattern
Implementation agent that executes a single task and creates handoff on completion
Idempotent Redundancy
Complete Claude Code hooks reference - input/output schemas, registration, testing patterns
Search GitHub code, repositories, issues, and PRs via MCP
Meta-skill workflow orchestrator for bug investigation and resolution. Routes to debug, implement, test, and commit based on scope.
Scrape web pages and extract content via Firecrawl MCP
Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
Environment Triage
Deep interview process to transform vague ideas into detailed specs. Works for technical and non-technical users.
Validate plan tech choices against current best practices and past precedent
Migration and upgrade review
Lightweight fixes and quick tweaks
General bug investigation and root cause analysis
Analyze Claude Code sessions using Braintrust logs
Documentation, handoffs, session summaries, and ledger management
Codebase exploration and pattern finding
Review implementation by comparing plan (intent) vs Braintrust session (reality) vs git diff (changes)
Document the codebase comprehensively
Performance profiling, race conditions, memory issues
Create implementation plans using research, best practices, and codebase analysis
Refactoring planning AND migration planning
External repository research and analysis
External research - web, docs, APIs with optional LLM
Analyze brownfield codebase and create initial continuity ledger
Extract perception changes from session thinking blocks and store as learnings
Multi-agent coordination for complex patterns
Integration and API review
Implementation and refactoring agent using TDD workflow
Refactoring and code transformation review
Release prep, version bumps, changelog generation
Investigate issues using codebase exploration, logs, and code search
Feature and implementation code review
Query the artifact index for precedent and guidance
Session analysis, precedent lookup, and learning extraction
Analyze Claude Code sessions using Braintrust logs
End-to-end and acceptance test execution
Unit and integration test execution and validation
Build Python agents using Agentica SDK - spawn agents, implement agentic functions, multi-agent orchestration
Security vulnerability analysis and testing