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Found 139 Skills
Fast web browsing and web app testing for AI coding agents via persistent headless Chromium daemon. Browse any URL, read page content, click elements, fill forms, run JavaScript, take screenshots, inspect CSS/DOM, capture console/network logs, and more. Ideal for verifying local dev servers, testing UI changes, and validating web app behavior end-to-end. ~100ms per command after first call. Works with Claude Code, Cursor, Cline, Windsurf, and any agent that can run Bash. No MCP, no Chrome extension — just fast CLI.
Install and configure react-grab to capture React component context (file path, component name, HTML markup) from any browser UI element for AI coding agents. Use when you want to point at a UI element in the browser and instantly copy its React component name, source file path, and HTML to clipboard for Claude Code, Cursor, Copilot, Gemini, or Codex. Triggers on: react-grab, grab, grab element context, copy component to ai, point and copy to claude, ui context clipboard, element to ai agent, click component copy, grab ui component, react component inspector, browser element context, component source file, copy element context, feed element to ai, element picker, grab react component, inspect element ai, component to clipboard, react devtools ai.
Disciplined spec-driven test-driven development workflow for building software with AI coding agents. Transforms ambiguous requests into verified implementations through structured specification, test derivation, and strict TDD. Handles greenfield projects, brownfield enhancements (with or without existing tests), refactors, and complex bug fixes with workflow-specific guidance for each. Use when the user requests a new feature, module, enhancement, refactor, API, data pipeline, CLI tool, or system with multiple requirements, edge cases, or unclear specifications. Also use for complex bug fixes requiring root cause analysis. Triggers on phrases like "add a feature", "implement", "build a new module", "build an API", "build a CLI", "build a data pipeline", "refactor", "fix this bug", "write tests for", "TDD", "test-first", "the requirements are unclear", "characterization tests", or "spec this out". Triggers when modifying code with adjacent test files (`tests/`, `*_test.py`, `*.test.ts`, `*.spec.ts`, `spec/`, `__tests__/`) or test framework config (pytest.ini, jest.config.*, go.mod with testing imports, Cargo.toml with [dev-dependencies], package.json with a test script). Triggers when the user mentions edge cases, invariants, acceptance criteria, EARS notation, or red-green-refactor. Do NOT use for simple one-line fixes, cosmetic changes, formatting, renames, dependency bumps, or tasks where requirements are already fully specified with tests provided.
Turn ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.
Bridge local AI coding agents (Claude Code, Cursor, Gemini CLI, Codex) to messaging platforms (Feishu, Telegram, Slack, Discord, DingTalk, WeChat Work, LINE) without a public IP.
ByteRover CLI (brv) - Persistent memory layer for AI coding agents with context trees, knowledge storage, and cloud sync
Post-completion self-review for coding agents that runs simplify, harden, and micro-documentation passes on non-trivial code changes. Use when: a coding task is complete in a general agent session and you want a bounded quality and security sweep before signaling done. For CI pipeline execution, use simplify-and-harden-ci.
Make application behavior visible to coding agents by exposing structured logs and telemetry. Use when asked to "add telemetry", "make logs accessible to agents", "add observability", "debug with logs", or when an agent needs to understand runtime behavior but has no way to query logs. Also use when debugging is difficult because there are no structured logs, when agent docs (CLAUDE.md, AGENTS.md) lack instructions for querying application logs, or when setting up logging infrastructure for a new or existing web application.
Local-first AI design tool that turns coding agents into design engines with 31 skills, 129 design systems, and multi-format export
Expert in using Claude Code Best (CCB) - a production-grade, debuggable fork of Anthropic's Claude Code CLI with enterprise features
Agent-agnostic visual feedback tool for AI coding agents to identify and annotate UI elements with structured selectors
Run multiple AI coding agent sessions in parallel using git worktrees — each agent isolated in its own worktree, working on a separate branch. Use this skill whenever the user wants to: run two or more AI agents simultaneously on different features or bugs, set up isolated agent workspaces in the same repo, push parallel branches to GitHub and open/update PRs, coordinate between concurrent agent sessions, or clean up after merging. Triggers on: "parallel agents", "multiple agent sessions", "git worktree", "run agents in parallel", "work on two things at once", "isolated agent workspace", "spin up another agent", or any request involving simultaneous AI-assisted development streams.