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Found 31 Skills
Harness engineering for AI coding agents — five subsystems, memory persistence, session continuity, verification workflows, scope control, lifecycle management.
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.
ByteRover CLI (brv) - Persistent memory layer for AI coding agents with context trees, knowledge storage, and cloud sync
Agent-agnostic visual feedback tool for AI coding agents to identify and annotate UI elements with structured selectors
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.
Curate, install, and manage Codex skills from the awesome-codex-skills collection for AI coding agents.
Connect AI coding agents to Figma designs via MCP to generate code from frames, extract design tokens, use Code Connect, and write directly to the canvas