Design, build, and debug AI agent systems — including multi-step reasoning loops, tool use, memory, planning, multi-agent orchestration, and autonomous workflows. Use this skill whenever the user wants to build an AI agent, agentic pipeline, or autonomous workflow; asks about agent architectures (ReAct…
Use when the user wants an agent session bridged to a phone, wants remote replies polled, or wants the agent to ask a phone for approval before sensitive actions.
Deep plan review with Pharaoh reconnaissance, wiring verification, and structured issue tracking. Use before implementing any feature, refactor, or significant code change. Enters plan mode (no code changes) and provides structured review with decision points.
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental…
Export Claude Code and Codex conversation history to Hugging Face as structured training data. Use when the user asks about exporting conversations, uploading to Hugging Face, configuring codeclaw, reviewing PII/secrets in exports, or managing their dataset.
Discover proven Outcomes and turn a rough request into one complete execution prompt for a fresh agent. Also author and validate source-owned Outcomes for Possible.
★not rated 11
changed 3d agoA30 tokens
originalMIT
Coordinate durable or cross-process work with local JSON mailboxes and vc teams commands. Use when messages must persist beyond one Codex session; prefer built-in Codex subagents for normal in-session delegation.
Research and stress-test open-source project names, from collision checks to launch-ready decisions. Use when the user asks to name or rename a project, compare candidate names, screen GitHub or package namespace risk, verify language or mythology claims, or improve SEO/GEO clarity. Perform live web and registry…
Use Grape MCP for Codex context continuity in coding repositories. Use when a task needs repeated-turn context, omitted context restore, stale-context checks, invalidation checks, or safe continuity across branch and dirty-worktree changes.
The Active Circuit Breaker & Cost Tracker for AI SaaS. Enforce hard API budgets, track GPT-4o/Claude costs, and stop runaway agents before they break your unit economics.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Choose the lightest Mastermind workflow that fits the risk, then create an evidence-grounded verified or strict task contract for delegated implementation. Direct work deliberately uses no task spec.
Build conversational AI chatbots with native Hebrew support, including WhatsApp Business API integration, Telegram bot scaffolding, web chat widgets, Hebrew NLP patterns, and RTL chat UI components. Prevents common Hebrew chatbot mistakes like broken RTL alignment, incorrect gender inflections, and poor tokenization…
Descobre e seleciona modelos de providers LLM de forma report-only: inventário read-only de modelos, docs oficiais, quota/billing/rate gates e shortlist para canary protegido. Use antes de adicionar providers, escolher modelos ou migrar monitores/roteamento.
Verifies that a feature is wired through all four layers (schema, API route, runtime, UI) before it may be called complete. Use when adding or auditing any feature — mirrors the connectivity-map method that caught the v1.21 autonomy gap.
Build or update UI screens, dashboards, forms, modals, and tables. Use when the subtask is primarily a frontend implementation — page layout, component composition, responsive design, interaction polish, or UI state wiring to existing APIs.
Complete workflow for AI agents using Chub: how to query docs efficiently and how to write structured annotations back to build persistent team knowledge.
Use when user explicitly requests planning with a scratchpad, or asks for persistent tracking of a complex task that the human can browse visually. Backs planning files with the scratch CLI so a pad's files are registered and viewable.
Routes user requests containing "remember", "recall", "checkpoint", "session", "todo", or "where were we" to the correct OpenEmpiric (OEM) MCP tool. Use when the user wants to persist, retrieve, or contextualize knowledge from project memory.
Reproduce a GitHub issue with a failing test, implement the minimal fix, verify tests pass, and open a pull request. Use this skill when given an issue number and a working checkout of the target repository.
★not rated 11▲
+2 13d agoA47 tokens
AGPL-3.0
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: