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Found 62 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.
Use when the user wants to author, refine, or audit a Product Requirements Document for AI coding agents. Walks through an 8-phase pipeline (Socratic discovery → PRD draft → acceptance criteria → adversarial review → task decomposition → AI-readiness gate → test generation → handoff). Triggers on "write a PRD", "spec this feature", "draft requirements", "prepare X for Claude/Cursor/Copilot/Windsurf/Aider to build", "audit my PRD", "is this PRD AI-ready", "score this spec".
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.
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics
Turn ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.
High-fidelity HTML design and prototype creation skill for AI coding agents — slide decks, interactive prototypes, landing pages, UI mockups, animations, and brand style cloning.
Harness engineering for AI coding agents — five subsystems, memory persistence, session continuity, verification workflows, scope control, lifecycle management.
ByteRover CLI (brv) - Persistent memory layer for AI coding agents with context trees, knowledge storage, and cloud sync
Local-first AI design tool that turns coding agents into design engines with 31 skills, 129 design systems, and multi-format export
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.
Spawn and manage parallel AI coding agents via tmux. Use when you need to orchestrate workers, delegate sub-tasks, run multi-agent improvement loops, or manage agent lifecycles with orca CLI commands like spawn, list, kill, steer, logs, and daemon.