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Found 1,746 Skills
Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.
Vercel Sandbox guidance — ephemeral Firecracker microVMs for running untrusted code safely. Supports AI agents, code generation, and experimentation. Use when executing user-generated or AI-generated code in isolation.
Extracts the full design soul, system, and agent rules from reference UI images. Use this skill when the user provides screenshots, Figma exports, or any UI reference images and wants the agent to design with the same soul, taste, feeling, and personality — not just copy colors and spacing. Marrow reads beneath the surface: it extracts the living core of a design — the decisions, proportions, restraint, and emotional intent that make a UI feel the way it does. Triggers on: /marrow, /extract-ui, /design-from-ref, /read-design, or any prompt like "extract the design system from these images", "make it look and feel like this", "get the rules from this UI", "build with the same soul", "match this design". Always use this skill when images are provided alongside a request to replicate, match, or be inspired by a design.
Use when the user asks about finding people, managing their network, creating signals/intents, discovering opportunities, or anything related to Index Network. Always active when the Index Network plugin is loaded.
Central skill registry and management system. Auto-loaded on every session. Auto-loaded on startup to provide skill discovery and invocation capabilities. Commands: - /skills - List all available skills with descriptions - /skill <name> - Load and activate a specific skill - /skill reload - Refresh skill registry - /skill help <name> - Show detailed help for a skill Capabilities: Auto-discovery of all skills in workspace, unified skill invocation via /skill command, skill registry with metadata and descriptions, version tracking and dependency management.
Checkpoint - Pre-publish review with multi-layer deep analysis. Triggers: Preparing to publish an npm package, requiring pre-release review, or checking code change quality. Review Layers: - Per-Change: In-depth analysis of each change group (up to 10 Agents) - Holistic: Parallel review by 5 roles (Architecture/Development/Testing/Security/Documentation) - Synthesis: 1 Agent summarizes review results Commands: - /把关 - Start pre-publish review - /把关 check - Check unpublished changes - /把关 version - Recommend version upgrade - /把关 report - Generate review report - /review - English command Capabilities: Unpublished change detection, in-depth per-change analysis, multi-role review, version recommendation, release risk assessment.
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.
Use when running Ralph-style iterative autonomous development. Triggers on /ralph or /loop commands, when autonomous iterative development is needed, when a project has specs and an implementation plan ready for iterative execution, or when deterministic context loading with subagent delegation and dual-condition exit gates is required. Orchestrates PLANNING, BUILDING, and STATUS cycles.
Analyze coding sessions to detect corrections and preferences, then propose targeted improvements to Skills used in the session. Use this skill when the user asks to "learn from this session", "update skills", or "remember this pattern". Extracts durable preferences and codifies them into the appropriate skill files.
OMC agent catalog, available tools, team pipeline routing, commit protocol, and skills registry. Auto-loads when delegating to agents, using OMC tools, orchestrating teams, making commits, or invoking skills.
Autonomous evolutionary code improvement engine with tournament selection
Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection