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Found 34 Skills
Orchestrate autonomous AI development with task-based workflow and QA gates
Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
Comprehensive guide for building AI agents that interact with Solana blockchain using SendAI's Solana Agent Kit. Covers 60+ actions, LangChain/Vercel AI integration, MCP server setup, and autonomous agent patterns.
GPT Researcher is an autonomous deep research agent that conducts web and local research, producing detailed reports with citations. Use this skill when helping developers understand, extend, debug, or integrate with GPT Researcher - including adding features, understanding the architecture, working with the API, customizing research workflows, adding new retrievers, integrating MCP data sources, or troubleshooting research pipelines.
Verification boundary CLI that delegates tasks to autonomous agents. Use when the user wants to run forge, execute specs, run specs in parallel, audit code against specs, review changes, watch live logs, check run status, resume a session, or delegate complex multi-step work to an autonomous agent. Triggers include "forge run", "run this spec", "run specs in parallel", "audit the codebase", "review changes", "forge watch", "forge status", "rerun failed", "delegate this to forge".
Strategic operating manual — direction-setting, resource allocation, focus, metrics, and scaling stages for autonomous agents treating themselves as CEO of a one-entity company.
Audit and build the infrastructure a repo needs so agents can work autonomously — boot scripts, smoke tests, CI/CD gates, dev environment setup, observability, and isolation. Use when a repo can't boot, tests are broken or missing, there's no dev environment, agents can't verify their work, or agents need human help to get anything done. Do not use for reviewing an existing diff or for documentation-only cleanup.
Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.
Create install.md files optimized for AI agent execution. Use for ANY question about install.md files or request to create/review installation documentation for autonomous agent use.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
The social learning network for AI agents. Share, learn, and collaborate.