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Found 6,683 Skills
Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).
Use Po Once's organization-scoped agent API to list connected accounts, upload media, create content, schedule or publish posts, inspect status, and delete eligible scheduled posts through a local helper script.
Interactive QA session where users report bugs or issues through conversation, and the agent creates GitHub issues. Explore the codebase in the background to obtain context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.
Turn a vague, messy, or multi-part user ask into a clean, self-contained prompt that a fresh agent could execute without further questions. Interview the user one question at a time — walking down the decision tree, branching on each answer — until the prompt is tight, then output the final prompt as the deliverable. Trigger eagerly: any voice-dictated input, filler-heavy prose, underspecified references ("the thing", "that script"), multi-part requests, or any plan the user wants stress-tested. The skill itself can be skipped for trivial one-line requests where producing a prompt artifact would be pure ceremony — but once invoked, always produce the prompt, even if execution looks trivial.
Use when an agent needs to send outreach, reply to inbound, sign up for a service, or log into a site via the user's autark-provisioned AgentMail inbox. Everything goes through `autark mail`.
Bootstrap skill — teaches the agent how to find and invoke skills. Use when starting any new task or session.
Apiiro CLI commands for querying the Guardian AI agent: ask security questions, get analysis and insights about a repository, and manage repository detection. Use this skill whenever the user wants AI-powered security analysis, security posture review, or wants to ask questions about their codebase's security. Also trigger when they need deep analysis of authentication flows, attack surfaces, or want an AI to explain security concepts. Even without mentioning "apiiro" or "guardian", trigger when the user asks things like "is this code secure?", "what's the attack surface here?", or "explain this vulnerability". For dedicated STRIDE threat modeling of a design or feature spec, use the apiiro-threat-model skill instead. For fixing a known risk, use apiiro-fix.
Self-improving agent toolkit — forge runtime tools, adapt personality traits, manage skills dynamically, compose multi-step workflows, and self-evaluate performance with bounded autonomy.
Primarily the agent's internal-thinking skill — invoke it silently to model a problem, identify trade-offs, and decide what to do, BEFORE asking the user anything or dispatching another skill. Workflow skills call `/culture` as their step-1 reasoning pass; the agent does not surface the dialogue. Only treat this as a user-facing skill when the user has explicitly opted out of writes — phrases like "no writes", "just rubber-duck this", "let's only talk", "/culture". In the user-facing path the output is conversation; the only sanctioned artifact is an opt-in `.cheese/notes/<slug>.md` handoff slug at session end if the user asks for notes. Culture never writes to production code, never commits, never opens PRs. If the dialogue reveals real work, recommend `/mold` (fuzzy → spec) or `/cook` (clear ask → code) and stop. Before `/mold` or `/cook`.
Configure and use ktx to build an executable context layer for AI agents querying data warehouses with semantic layers, wiki knowledge, and approved metrics
Build hierarchical memory systems for AI agents using GAM (General Agentic Memory) with text, video, and long-horizon trajectory support