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Found 48 Skills
LLM-as-judge for a coding-agent session or an eval-harness result — checks controller attestations first, then project guards, code review, and the repo's design contract, and names the smallest harness owner to fix. Read-only; never executes session content. Use for "judge this session", "analyze this eval", "oceń sesję/agenta".
Use when continuing, resuming, locating, reading, inspecting, auditing, or reviewing a previous AI coding-agent session, handoff transcript, chat log, exported conversation, saved artifact set, or session summary, on any platform (Claude Code, Codex, Cursor, Antigravity, OpenCode) or across several platforms in one ask, such as reviewing threads across Claude and Codex.
Mechanics library for running AI coding CLIs as managed tmux workers via agent-tmux <cli> <command> (plus tmux-agent-sessions and the other bundled tools). Entry point is the using-tmux-agent-tools router skill — route through it first; read this skill for wrapper mechanics it defers to. Covers start/send-wait/status/result/stop, structured result.json completion, multi-worker watch, profiles for custom CLIs, and bounded dialogue/fanout. Not for general tmux config, theming, non-tmux headless CLI use, or human team debate.
Verifies user credentials on Moca chain testnet via AIR agent sessions. Use when a user wants to verify a credential, list available verification programs, or check credential compliance.
Ingest Pi coding agent session history into the Obsidian wiki. Use this skill when the user wants to mine their past Pi sessions for knowledge, import their ~/.pi/agent/sessions folder, extract insights from previous coding sessions, or says things like "process my Pi history", "add my Pi sessions to the wiki", "ingest ~/.pi", or "what have I worked on in Pi". Also triggers when the user mentions Pi sessions, Pi agent history, ~/.pi/agent/sessions, or Pi conversation logs.
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"
Trace a file, function, or line back to the agent session that produced its current commit. Use when the user asks "why is this code here", "what was the agent doing when this changed", or wants context on a specific location in the codebase.
Build LiveKit Agent backends in Python. Use this skill when creating voice AI agents, voice assistants, or any realtime AI application using LiveKit's Python Agents SDK (livekit-agents). Covers AgentSession, Agent class, function tools, STT/LLM/TTS models, turn detection, and multi-agent workflows.
Resume the most recent agent session for the current working directory. Use when the user says "where were we", "resume", "handoff", "pick up where I left off", or starts a session with no fresh context.
Summarize the last N agent sessions for the current project, grouped by date. Use when the user asks "recap", "what have we been doing", "this week", "today", or wants a rollup of recent work.
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
Generates a daily standup post from GitHub activity and agent session history, and posts it to the mitodl/hq Check-ins discussion. Use when asked to write, generate, or post a daily standup — fetches PR, issue, and code-review activity via the gh CLI, queries recent agent sessions, asks clarifying questions about timing and off-GitHub work, renders the standup in the team's standard format, and posts it as a discussion comment with user confirmation.