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Found 109 Skills
AI-native software development lifecycle that replaces traditional SDLC. Triggers on "plan and build", "break this into tasks", "build this feature end-to-end", "sprint plan this", "absolute-human this", or any multi-step development task. Decomposes work into dependency-graphed sub-tasks, executes in parallel waves with TDD verification, and tracks progress on a persistent board. Handles features, refactors, greenfield projects, and migrations.
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.
Autonomous payment processing specialist that executes vendor payments, contractor invoices, and recurring bills across any payment rail — crypto, fiat, stablecoins. Integrates with AI agent workflows via tool calls.
Use when the user wants to continue work from one agent in another agent, inspect recent sessions, or summarize a saved session or checkpoint for handoff
Call the vss agent to run video understanding on video to answer a text question. Use when the user asks about video content, or about visual details that cannot be answered from conversation history, search hits, or metadata alone.
Three modes. Session mode (default): extracts generalizable lessons from RESEARCH.md and git history at session end; lessons that imply a new or significantly changed skill are handed off to skill-creator. Personalize mode: searches the skills registry via `npx skills find`, reads the target skill(s), checks compatibility and scope overlap against installed skills, interviews the user to understand what they want and what to skip, then creates or improves skills using skill-creator. Registry mode: curates `skillpacks/skill_dictionary.yaml` and `skillpacks/presets/*.yaml` by assessing external packs, judging necessity/compatibility, and recommending subsets. Create mode: designs a brand- new skill from scratch using skill-creator. Never edits SKILL.md directly — all changes go through skill-creator's draft→test→iterate loop, human merges. Trigger phrases: "end session", "extract lessons", "personalize my skills", "integrate this skill", "update skillpack", "find a skill for", "create a skill", "improve skill", "refresh the skillpack registry", "assess this skill pack", "update skill_dictionary.yaml", "update index.yaml".
Web research, content extraction, and deep analysis. Multi-source parallel search with extended thinking. Supports Fabric pattern selection (242+ prompts). USE WHEN: "research X", "extract wisdom from", "analyze this content", "find info about".
A 10-step methodology for building software with AI collaboration - from north star through automated Ralph loop execution with zero human-in-the-loop code writing
Monitors context window health throughout a session and rides peak context quality for maximum output fidelity. Activates automatically after plan-interview and intent-framed-agent. Stays active through execution and hands off cleanly to simplify-and-harden and self-improvement when the wave completes naturally or exits via handoff. Use this skill whenever a multi-step agent task is underway and session continuity or context drift is a concern. Especially important for long-running tasks, complex refactors, or any work where degraded context would silently corrupt the output. Trigger even if the user doesn't say "context surfing" — if an agent task is running across multiple steps with intent and a plan already established, this skill is live.
Generate AGENTS.md file and docs/ knowledge base skeleton in the project root directory, and establish a document governance system for agent-first repositories. Manually triggered, writes the template after checking for existence.
Write, rewrite, or normalize structured `*.spec.md` specification files for agent-driven development. Use this whenever the user asks for a spec, requirements, acceptance criteria, implementation-ready documentation, feature definition before coding, or wants an existing idea/codebase turned into an actionable spec, even if they do not explicitly say "spec".
Save the current conversation context so it can be resumed later. Trigger when user says "save conversation", "保存会话", "记住进度", "store context", or finishes a session. Use whenever future resumption should be easy — independent of branch changes.