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Found 5,666 Skills
Event-sourced task system for agent collaboration. Use when managing tasks, tracking work, handing off between agents, checking task queues, or reporting progress. Provides both MCP tools and a CLI (ql).
Set up and improve harness engineering (AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering) for AI-agent-friendly codebases. Triggers on: new/empty project setup for AI agents, AGENTS.md or CLAUDE.md creation, harness engineering questions, making agents work better on a codebase. ALSO triggers when users are frustrated or complaining about agent quality — e.g. 'the agent keeps ignoring conventions', 'it never follows instructions', 'why does it keep doing X', 'the agent is broken' — because poor agent output almost always signals harness gaps, not model problems. Covers: context engineering, architectural constraints, multi-agent coordination, evaluation, long-running agent harness, and diagnosis of agent quality issues.
Use a persistent Codex sidecar thread from the local `codex-sidecar` CLI for design review, implementation advice, debugging, and context-preserving follow-up questions while keeping the current agent as the primary executor.
Top-tier software architect agent for complex multi-stage project development. This skill embodies the role of a senior software architect who decomposes complex tasks into structured sub-modules, iterates each component until excellence is achieved, enforces strict quality gates between phases, and produces documentation compliant with all skill standards. Core Philosophy: "Design once, iterate until perfect, then move forward." Triggers when: You need to design architecture for a complex multi-stage project, decompose requirements into modules, or establish quality gates for development phases. Commands: - /architect design <task> - Full architecture design for a task - /architect phase <n> - Execute specific phase - /architect iterate <module> - Iterate on a specific module - /architect status - Show current architecture status - /architect review - Review and validate architecture Six phases: Requirement Analysis, Architecture Design, Task Decomposition, Iterative Development, Integration & Validation, Documentation Generation. Each phase has strict exit criteria.
Guide for conducting thorough, multi-source research and producing comprehensive, well-sourced reports. Powered by AnyCap -- the capability runtime that equips AI agents with web search (including AI Grounded citations), web crawl, image generation, cloud storage, and one-click web publishing through a single CLI. Use when the user asks for deep research, competitive analysis, market research, technical deep dive, literature review, technology comparison, or any task requiring multi-source information gathering and synthesis. Also use when users say "investigate", "survey the landscape", "compare X vs Y", "state of the art", "write a report on", "look into", "find out about", "analyze the market", or any inquiry that needs more than a single search. Trigger on mentions of research, analysis, investigation, comparison, report, survey, or deep dive.
Build AI phone agents with AgentPhone API. Use when the user wants to make phone calls, send/receive SMS, manage phone numbers, create voice agents, set up webhooks, or check usage — anything related to telephony, phone numbers, or voice AI.
Agent skill for coordinator-swarm-init - invoke with $agent-coordinator-swarm-init
Reviews, curates, and maintains the Forge library of agents, skills, and templates. Performs deduplication analysis, staleness detection, quality promotion, and orphan reference checking. Produces structured review reports with actionable recommendations for merging, archiving, or promoting library items. Use this skill when the user wants to review the library, clean up agents or skills, check what's available, find duplicates, trim unused items, see library statistics, or says "what's in my library?" Also triggers on scheduled review intervals or when the library grows beyond 20 items. Do NOT use for creating new agents (use Agent Creator), creating skills (use Skill Creator), or planning teams (use Mission Planner).
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).
Enforces complete execution, mode-aware delivery, compact sub-agent communication, independent agent-review gating, validation, and reporting for implementation, bugfix, hardening, documentation, specification, architecture, design, review, and post-mortem tasks. Use whenever work must be completed, reviewed, validated, or documented through an explicit execution mode instead of handled ad hoc.
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.
Reference skill for Zoom Virtual Agent. Use after routing to a virtual-agent workflow when implementing web embeds, Android or iOS wrapper integrations, knowledge-base sync, lifecycle handling, or troubleshooting.