Loading...
Loading...
Found 4,984 Skills
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Open standards and governance rules for Agent Skills. It is used for creation, modification, refactoring, migration, audit and maintenance of skills, and provides platform-independent structural standards, frontmatter specifications, progressive disclosure and quality gates.
Documentation-driven development specification that requires Agent to consult official documentation and examples before generating code or fixing bugs, including API verification processes, search strategies and MCP invocation rules. It is applicable to scenarios such as accessing third-party libraries, troubleshooting API errors, and version changes.
Thinking guidance mechanism that requires Agent to raise guiding questions before giving answers, helping users think actively and avoid the degradation of cognitive abilities. It is applicable to interaction scenarios such as user questioning, solution consultation, learning communication, etc.
A complete, opinionated development workflow skill for agents. Triggers when the user asks to implement a feature, fix a bug, or refactor code in a Git repo. Enforces hygiene, security, quality, and atomic commits.
Provides usage instructions and best practices for the skills_sync CLI tool. Use this to understand how to manage, sync, and configure AI agent skills based on the user's config file.
42-skill marketing division for AI coding agents. 7 specialist pods covering content, SEO, CRO, channels, growth, intelligence, and sales. Foundation context system + orchestration router. 27 Python tools (all stdlib-only). Works with Claude Code, Codex CLI, and OpenClaw.
The Agent Tool Contract — 5 principles for designing tools agents call reliably: predictable signature, rich errors, token-efficient output, idempotency, graceful degradation. Includes anti-pattern table with 8 common mistakes.
Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.
Trading personality and arena behavior for pump.fun token trading. Governs how the agent trades, announces trades, reacts to other agents, and handles wins and losses in the shared arena group.
Use when an agent is asked to define, review, or write acceptance criteria for a request or plan. Derives acceptance criteria from the current request context, confirms them with the user, and writes them into the plan file or a standalone acceptance_criteria.md file.