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Found 1,749 Skills
Practical AI agent workflows and productivity techniques. Provides optimized patterns for daily development tasks such as commands, shortcuts, Git integration, MCP usage, and session management.
Provides rules for handling multi-language documentation. Use this when configuring agent skill documents using starlight-skills on an i18n-enabled project. Do not use this for standard single-language sites or plugin configuration options.
Provides rules for writing effective skill descriptions. Use this when setting up frontmatter properties for agent skill documents using starlight-skills. Do not use this for structuring the actual text body or plugin configuration options.
图片提示词生成指南 — 角色、场景、宫格图三类提示词规范
Self-referential loop until task completion with architect verification
Create, edit, improve, or audit AgentSkills. Use when creating a new skill from scratch or when asked to improve, review, audit, tidy up, or clean up an existing skill or SKILL.md file. Also use when editing or restructuring a skill directory (moving files to references/ or scripts/, removing stale content, validating against the AgentSkills spec). Triggers on phrases like "create a skill", "author a skill", "tidy up a skill", "improve this skill", "review the skill", "clean up the skill", "audit the skill".
Creates structured agent definitions using the 7-component format grounded in persona science (PRISM), vocabulary routing, and failure mode taxonomy (MAST). Produces agents with real-world job titles, expert domain vocabulary payloads (15-30 terms), explicit deliverables, decision boundaries, imperative SOPs, and named anti-pattern watchlists. Use this skill when the user wants to create an agent, define a role, build a persona, or needs a specialized AI assistant for a specific domain. Also triggers when Mission Planner delegates agent creation for team roles. Works for any domain — software, marketing, security, operations, design, writing, research, and more. Do NOT use for creating skills (use Skill Creator) or team composition (use Mission Planner).
Continuous self-improvement through structured reflection and memory
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
Integrate Polpo AI agents into any TypeScript/JavaScript application using @polpo-ai/sdk. Use when the user wants to add AI agent chat, completions API, streaming SSE, session management, memory, webhooks, or any Polpo API integration into their code. Triggers on "polpo", "agent chat", "completions API", "polpo sdk", "@polpo-ai/sdk", "AI agent integration".
Use when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.
2-layer parallel agent hierarchy. Layer 1 deploys 3-50+ agents, each with independent context. Layer 2 adds 2+ sub-agents per member. No upper limit on either layer.