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Found 26 Skills
Interactively onboard a project to agent-driven development by running a structured interview and generating a complete AGENTS.md (or CLAUDE.md). Use this skill whenever a user mentions "AGENTS.md", "CLAUDE.md", "agent behavior", "agent instructions", "agent config", "set up agent rules", "onboard agent", "configure claude code", "agent guardrails", "agent workflow", or asks how to tell an AI agent how to behave in their project — even if they just say "help me write AGENTS.md" or "what should go in CLAUDE.md". Always prefer this skill over ad-hoc agent instruction generation.
Use Frappe Manager (FM) for Docker-based development and testing environments. Use when setting up local dev, running isolated tests, or managing agent-driven Frappe development workflows.
Visual HTML canvas sandbox for agent-driven UI and live previews
Drive a spec-first workflow for substantial features by writing PRODUCT.md before implementation, writing TECH.md when warranted, and keeping both specs updated as implementation evolves. Use when starting a significant feature, planning agent-driven implementation, or when the user wants product and tech specs checked into source control.
Complete setup for automated agent-driven development. Define features as user stories with testable acceptance criteria, then run AI agents in a loop until all stories pass.
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
Set up or update the agent-first engineering harness for any repository. Implements the complete scaffolding that makes AI coding agents effective: knowledge maps (AGENTS.md as a concise TOC), structured documentation, architecture boundaries, enforcement rules (.harness/*.yml specs), quality scoring, and process patterns for agent-driven development. Use this skill whenever someone wants to make a repo agent-ready, set up AGENTS.md or docs/ structure, define domain boundaries or golden principles, generate .harness/ configuration, audit agent readiness, or update an existing harness. Also trigger when a user reports problems with agent effectiveness, context management, or architectural drift — these are symptoms of a missing or stale harness. Trigger on: "harness this repo", "set up harness", "agent-first setup", "make this agent-ready", "update the harness", "assess agent readiness", "set up AGENTS.md", "organize for agents", or any discussion about structuring a codebase for AI agent workflows.
Use this skill when working with A2UI (Agent-to-User Interface) - Google's open protocol for agent-driven declarative UIs. Triggers on tasks involving A2UI message generation, component catalogs, data binding, surface management, renderer development, custom components, or integrating A2UI with A2A Protocol, AG UI, or agent frameworks like Google ADK. Covers building agents that generate A2UI JSON, setting up client renderers (Lit, React, Angular, Flutter), creating custom catalogs, and handling client-to-server actions.
Frontend website debugging toolkit using Chrome DevTools Protocol with Playwright/WebKit fallbacks. Use this skill when: (1) Debugging CSS, HTML, or JavaScript issues on a webpage, (2) Taking screenshots to verify visual changes, (3) Inspecting DOM structure or console errors, (4) Testing responsive layouts, (5) Extracting selectors for automation, (6) Self-debugging frontend work Claude has created, (7) User says "debug this page", "check my site", "why doesn't this look right", or "fix the frontend". Supports Chrome (primary) and Safari/WebKit (via Playwright). Designed for agent-driven debugging loops.
Solana Kit (JavaScript SDK) — RPC, signers, transactions, accounts, codecs, instruction plans, and program clients for agent-driven Solana tooling.
Solana blockchain development — core concepts, clients, RPC, tokens, and payments for agent-driven tooling.
Write, rewrite, or normalize structured `*.spec.md` specification files for agent-driven development. Use this whenever the user asks for a spec, requirements, acceptance criteria, implementation-ready documentation, feature definition before coding, or wants an existing idea/codebase turned into an actionable spec, even if they do not explicitly say "spec".