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Found 520 Skills
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
Multi-model agent orchestration using specialized agents for planning, coding, research, math/science, visual analysis, and adversarial review. Use when tasks are complex enough to benefit from different models' strengths, when you want adversarial review to catch blind spots, or when coordinating multi-step workflows across agent roles. Triggers on complex projects, multi-step tasks, architecture decisions, or when explicitly requested.
Adaptive exploration pipeline that integrates /brainstorm, /think, and /red-team with intelligent pivoting. Unlike /deepthink (which takes a fixed idea and iterates), /prospect starts with divergent brainstorming, picks the most promising vein, runs deep analysis, and — crucially — can PIVOT back to divergent thinking when: the idea dies under red-team, an adjacent opportunity surfaces during analysis, or the research reveals the real opportunity is elsewhere. Produces a prospecting report: the landscape explored, veins assayed, pivots taken, and the final stake with conviction. Use when the user says "prospect", "explore this space", "find opportunities", "what should I build", "explore and analyze", or has a domain/trend they want to both explore AND evaluate.
Create, update, and maintain skills in the canonical .skills/internal/ directory. Includes step-by-step directives for agents to work with users, validate skill structure, and sync changes across agent directories. Use when users want to create new skills, update existing ones, or need guidance on skill authoring.
A hybrid pattern where the system pauses execution to request human approval, input, or disambiguation before proceeding with critical actions. Use when user asks to "add human approval", "require human review", "human-in-the-loop", or mentions approval workflows, human oversight, or escalation.
Operate on @spec facts — implement them in code, then tag @implemented. Use when asked to implement facts, implement the spec, build from the fact sheet, make facts true, or work through unimplemented requirements.
Produces a compact briefing document for an AFK agent taking on a specific slice. Use after create-prd or create-issues, immediately before handing work to a coding agent. Do NOT interview the user — synthesise from the current context.
Review and approve (or reject) pending playbook update proposals from the playbook-monitor agent and apply approved changes to the practice profile. Use when the playbook-monitor agent has surfaced proposals, when the user says "review playbook proposals", "what playbook updates are pending", or wants to step through deviation-driven playbook changes.
A-share Market Daily Review System. Actively invoked when users mention needs such as market review, market analysis, or tomorrow's market prediction. Covers: Market Environment, Sentiment Cycle, Main Line Identification, Capital Monitoring, Post-Market Variables, Tomorrow's Combat Map. For research reference only, does not constitute securities investment consulting business or investment advice.
Report coding-agent progress, questions, decisions, blockers, tests, PRs, human replies, inbox instructions, and handoffs to the Agora coordination server. Use for every coding task when AGORA_URL is set, especially at session start, before risky or shared edits, when blocked, when asking for human or agent input, after running tests or verification, when opening or updating PRs, when polling for human replies or instructions, and before the final response.
Use when asking about Rust versions or crate info. Keywords: latest version, what's new, changelog, Rust 1.x, Rust release, stable, nightly, crate info, crates.io, lib.rs, docs.rs, API documentation, crate features, dependencies, which crate, what version, Rust edition, edition 2021, edition 2024, cargo add, cargo update, 最新版本, 版本号, 稳定版, 最新, 哪个版本, crate 信息, 文档, 依赖, Rust 版本, 新特性, 有什么特性
NEAR AI agent development and integration. Use when building AI agents on NEAR, integrating AI models, creating agent workflows, or implementing AI-powered dApps on NEAR Protocol.