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Found 2,225 Skills
Mechanize Pattern 15 — the seven-pass adversarial review protocol for academic manuscripts. Spawns 7 forked subagents in parallel (abstract, intro, methods, results, robustness, prose, citations), then synthesizes a prioritized revision checklist. Use for submission-ready or R&R-stage papers where single-pass review isn't enough.
Creates project constitution files (CLAUDE.md/AGENTS.md) that serve as always-loaded context for coding agents. Use when setting up a new project for spec-driven development, configuring agent instructions, writing CLAUDE.md or AGENTS.md, or establishing project-wide coding standards and constraints.
Create accurate Japanese UI DESIGN.md files for AI agents with proper CJK typography, font stacks, line-height, kinsoku shori, and mixed typesetting rules.
Architecture patterns and best practices for giving AI agents email capabilities. Use when designing how agents send, receive, and manage email conversations, building two-way communication loops, implementing human-in-the-loop approval with drafts, choosing between WebSockets and webhooks, setting up multi-agent email topologies, handling OTP and verification flows, or securing agent email against prompt injection.
Use when the user wants to initialize, switch, inspect, optimize, export, or diagnose a role bundle with /roleMe.
AI-automated penetration testing and general problem-solving system that achieved unique AK (All Killed) in Tencent Cloud Hackathon intelligent penetration challenge
Supernormal platform help — AI agent for agencies that turns meeting context into deliverables (pitch decks, briefs, emails, spreadsheets). Use when setting up Supernormal desktop app for bot-free recording, Supernormal AI agents not generating deliverables, Supernormal credits running out or credit system confusion, Supernormal bot joining Zoom calls uninvited, comparing Supernormal to Sembly or Fathom or Fireflies for agency work, Supernormal MCP integration, Supernormal Slack or CRM sync to HubSpot or Salesforce, or Supernormal transcription accuracy issues with accents. Do NOT use for choosing between AI note-takers (use /sales-note-taker) or general meeting transcript API integration (use /sales-note-taker).
Li — Knowledge Manager for Ane's library and MEL Wiki. Use when Ane needs to catalog, retrieve, or reorganize documents in the personal knowledge library, or query/maintain the MEL Wiki. Handles INGEST, QUERY, and LINT operations. Does not answer domain questions — retrieves and organizes knowledge for other agents and Ane.
Build command-line interfaces for AI agents. Covers arguments, flags, subcommands, help text, output formats, error messages, exit codes, config/env precedence, and safe/dry-run behavior. Use when building a new CLI or refactoring an existing one for agent use.
Universal task dispatcher. Start, route, and execute any task through the development workflow (Steps 0-9). Invoke on every task — /task <description>, /task
Unified review skill — auto-detects plan or code, assembles the right panel, runs a bounded review-fix loop with severity gating. Use when a plan or implementation needs review.
Use the unified Opper SDKs (`opperai` package for both Python and TypeScript, with built-in agent support) for AI task completion, structured output with Pydantic / Zod / JSON Schema, knowledge base semantic search, streaming, tracing, tool use, and multi-agent composition. Use this skill whenever the user is writing Python or TypeScript code that imports `opperai`, builds an Opper agent, or asks how to do anything Opper-related in code — even if they don't explicitly name the SDK. Both languages live in one repo with parallel numbered examples; agents are part of the SDK, not a separate package.