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Found 134 Skills
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
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.
Convert structured UX specs and product context into a sequenced prompts.md file for Claude Code. Use when a user has completed upstream design thinking (problem framing, PRD, UX spec) and needs to translate that into step-by-step prompts that coding agents can execute incrementally. This skill bridges design artifacts to code generation.
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