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Found 13,475 Skills
This skill should be used to summarize coaching or therapy session transcripts after a Fathom/Granola sync. The agent analyzes the transcript itself (no API key, runs on the subscription) and appends key insights, decisions, action items, and trail connections. Supports quick extraction or deep analysis with cross-session pattern detection.
Session mode: act as orchestrator brain only. Research and implementation go to cheaper-model subagents; the orchestrator scopes, briefs, verifies, and judges. User-invoked with the task as the argument.
Use this skill whenever a user wants to run, install, configure, or understand open-ralph-wiggum (ralph). This skill can be used by any AI assistant or IDE agent (GitHub Copilot, Claude Code, Cursor, Windsurf, etc.). Triggers on: "ralph", "ralph wiggum", "agentic loop", "iterative AI loop", "autonomous coding loop", "how to install ralph", "how to use ralph with Claude Code / Codex / Copilot / OpenCode", "ralph --agent", "ralph --tasks", "ralph --status", "--max-iterations", "--rotation", "how do I run ralph in VS Code / Cursor / JetBrains / Neovim", or any question about looping an AI coding agent until a task is done. Even if the user doesn't say "ralph" explicitly — if they want to run an AI agent in a loop until a promise tag appears in its output, use this skill.
Use this skill when creating or deploying a TON agentic wallet. It generates operator keys and deploys an on-chain agentic wallet. Also use when setting up a new agent wallet, onboarding a wallet, or when any wallet operation fails because no wallet is configured. This skill is a prerequisite before sending, swapping, or managing assets on TON.
Delegate implementation work to the coder agent. Provide requirements or feature file path.
GPT Image 2 prompt gallery, agentic skill, and CLI for OpenAI image generation and editing with curated prompts and reference workflows
Use when building AI-powered features with CopilotKit v2 -- adding chat interfaces, registering frontend tools, sharing application context with agents, handling agent interrupts, and working with the CopilotKit runtime.
Pull items from Solo Scope RSS (https://www.mixdao.world/feed), organize them into 3 to 6 categories by topic, generate a 140-word core value summary for each category, and output a briefing with the original title and URL of each item. The Agent will independently complete the pulling, organizing, and briefing writing. Trigger examples: "Do Solo Scope", "olo Scope", "Organize mixdao feed", "RSS categorized briefing".
Manages organizational guidelines, policies, and best practices as governance variables accessible to all AI agents via SmartContext. Use when working with company rules, brand voice, compliance policies, playbooks, or when any task needs organizational context before proceeding.
For use when students **have completed WG-12 to WG-21** (single-file consolidation blueprint) and are working on **WG-22 Code Splitting** (`agent_core.py` + `main.py`). **First message in a new session**: Display PEAS brand screen and confirm readiness first; after confirmation, **lay out the context** before proceeding to requirement clarification. If **`prompts/` or `templates/`** are missing, copy them from `references/project_assets/` to the project root. Process: Spec Alignment (2d′) → Six-column Contract → **In-session Handoff Implementation** → Acceptance. Starting point: starter_main_wg21.py; Standard reference: reference_agent_core.py + reference_main.py. Triggers: peas-workshop-advanced-coach, PEAS workshop advanced coach, WG-22, code splitting coach, Agent.chat.
Harvest coding-agent session transcripts already on disk (Claude Code, Codex, OpenCode, Cursor, Pi) and extract durable knowledge — topics, people, facts, events, quotes — into whatever persistent memory the agent can reach. Cursor-tracked, budgeted, read-only on sources. Use when asked to collect/import/mine session history into memory, build memory from past sessions, or as a scheduled task. Composes with memory-gardener, which tends what this skill plants.
This skill should be used when dispatching autonomous development or review tasks from GitHub issues. Covers scanning for new issues with the 'autonomous' label, dispatching dev-new/dev-resume/review processes, dependency checking, retry counting, stale process detection, and concurrency limiting. Use when asked to "run the dispatcher", "scan for pending issues", "dispatch autonomous tasks", "check stale agents", or "set up the dispatch cron".