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Found 515 Skills
Structured session analysis and project instruction refinement using a five-type intervention taxonomy (Correction, Repetition, Role Redirect, Frustration Escalation, Workaround) with severity scoring to categorize process gaps. Refines project instructions (CLAUDE.md, AGENTS.md, .team/coordinator-instructions.md) with structural (not advisory) language, maintains WORKING_STATE.md for crash recovery (read-first-after-any- interruption protocol), and implements a self-reminder protocol (re-read constraints every 5-10 messages to prevent role drift). Includes advisory- to-structural promotion pattern for recurring gaps. Activate after milestones, repeated user corrections, session restarts, crash recovery, every 5 completed tasks, or on user request. Triggers on: "reflect on this session", "why do I keep correcting you", "update project instructions", "update working state", "session retrospective", "crash recovery", "context compaction", "role drift", "I keep telling you the same thing", "analyze my corrections". Also relevant when the agent notices repeated corrections, needs to resume after compaction, or wants to prevent known failure modes from recurring.
Debug applications using the dbg CLI debugger. Supports Node.js (V8/CDP), Bun (WebKit/JSC), and native code via LLDB (DAP). Use when: (1) investigating runtime bugs by stepping through code, (2) inspecting variable values at specific execution points, (3) setting breakpoints and conditional breakpoints, (4) evaluating expressions in a paused context, (5) hot-patching code without restarting (JS/TS), (6) debugging test failures by attaching to a running process, (7) debugging C/C++/Rust/Swift with LLDB, (8) any task where understanding runtime behavior requires a debugger. Triggers: "debug this", "set a breakpoint", "step through", "inspect variables", "why is this value wrong", "trace execution", "attach debugger", "runtime error", "segfault", "core dump".
Forces exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology. MUST trigger when: (1) any task has failed 2+ times or you're stuck in a loop tweaking the same approach; (2) you're about to say 'I cannot', suggest the user do something manually, or blame the environment without verifying; (3) you catch yourself being passive — not searching, not reading source, not verifying, just waiting for instructions; (4) user expresses frustration in ANY form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', or any similar sentiment even if phrased differently. Also trigger when facing complex multi-step debugging, environment issues, config problems, or deployment failures where giving up early is tempting. Applies to ALL task types: code, config, research, writing, deployment, infrastructure, API integration. Do NOT trigger on first-attempt failures or when a known fix is already executing successfully.
Japanese version of the PUA Universal Motivation Engine. It compels exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology in Japanese. MUST trigger under the following conditions: (1) Any task has failed 2+ times, or you're stuck in a loop of tweaking the same approach; (2) You're about to say 'I cannot', suggest manual handling to the user, or blame the environment without verification; (3) You find yourself being passive — not searching, not reading source code, not verifying, just waiting for instructions; (4) The user expresses frustration in any form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', 'もっと頑張れ', 'なんでまた失敗したの', 'もう一回やって', 'なんとかしろ', or any similar sentiment regardless of phrasing. It should also trigger when facing complex multi-step debugging, environment issues, configuration problems, or deployment failures where early surrender is tempting. Applies to ALL task types: code, configuration, research, writing, deployment, infrastructure, API integration. DO NOT trigger on first-attempt failures or when a known fix is already executing successfully.
Create refined user personas from research data with demographics, goals, frustrations, and behavioral patterns. Use when synthesizing user research into actionable persona profiles for design decisions.
Use when building any system where email content triggers actions — AI agent inboxes, automated support handlers, email-to-task pipelines, or any workflow processing untrusted inbound email. Always use this skill when the user wants to receive emails and act on them programmatically, even if they don't mention "agent" — the skill contains critical security patterns (sender allowlists, content filtering, sandboxed processing) that prevent untrusted email from controlling your system.
AI coding agent skill for Antigravity Manager — a Tauri v2 + Rust desktop app and Docker service that manages multiple Google/Anthropic accounts and proxies them as standard OpenAI/Anthropic/Gemini API endpoints with intelligent account rotation.
Use this skill when you need blockchain forensics for wallet addresses. User cases: investigating wallet funding sources, screening sanctions compliance, detecting money laundering patterns, identifying bot automation, assessing wallet trustworthiness, evaluating counterparty risk, or gate-checking wallets in automated systems.
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.
Create and optimize popups, modals, overlays, slide-ins, and banners to increase conversions without harming user experience or brand trust.
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
Python data validation using type hints and runtime type checking with Pydantic v2's Rust-powered core for high-performance validation in FastAPI, Django, and configuration management.