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Found 2,169 Skills
Use when the user wants to store, retrieve, search, or manage files in agent-fs — an agent-first filesystem backed by S3. Triggers on: "save this to agent-fs", "find that file", "store this document", "search agent-fs", "list my files", "show version history", "revert file", "set up agent-fs", "get a signed url", "share this file", "manage members", "invite user", "list members", "remove member", "update role", file persistence for agents, shared agent filesystem, or any mention of the agent-fs CLI. Also use when the user needs to manage drives, manage org/drive members, generate presigned URLs, check recent activity, or use semantic search across stored files. Also use when the user wants to run SQL over stored data files ("query this csv", "sql over my files", "duckdb", "aggregate the parquet file", "query the sqlite db", "join these spreadsheets"). Also use when the user wants to mount or unmount agent-fs as a Linux FUSE filesystem ("mount agent-fs", "fuse mount", "fuse", "remote mount", "sandbox mount", "expose drives as files", "use cat/grep/mv on my agent-fs files", "umount the drive", "mount a remote drive", "mount from sprite", "mount from e2b", "mount from hetzner"). Also use when the user wants to use agent-fs as a just-bash filesystem. Also use when the user wants to set up agent-fs without Docker or S3 ("local filesystem backend", "filesystem storage", "no docker", "onboard --filesystem", "store files on disk"). If the user mentions agent-fs in any context, always consult this skill.
Use this skill when the user wants to create, read, update, or delete traditional automations (if/then rules) or AI automations (prompt-driven). Covers 16 MCP tools. For AI agents (conversational), see skills/ai-agents/.
Use this skill for any question or action about the user's AI/GenAI applications or agents — their behavior, prompts/responses, quality, hallucinations, guardrails, security, cost/tokens, errors, evaluations/policies, model pricing, or configuration — including comparing or tracking agents over time. It covers both analyzing AI telemetry (GenAI spans) and managing AI Center config via the `cx ai-center` commands.
Default guidance for building AI agents. Use for generic requests to build, create, scaffold, design, architect, or implement an AI agent, agent app, tool-calling agent, durable agent, multi-agent system, or scheduled agent. Not for code-review or incident-investigation agent products.
Initialize projects with safe, preference-driven scaffolds, docs, AI instructions, quality gates, GitHub setup, and design baselines. Use when starting a repo or non-destructively adding conventions. NOT for product features, agents, MCP servers, cloud provisioning, or destructive migrations.
Orchestrator for setting up Agentforce in Salesforce Service Cloud ITSM — Agentforce Studio enablement, the IT Service Fulfiller agent lifecycle, and the IT Service Employee agent lifecycle. Use when the user asks to set up Agentforce for ITSM, enable Studio and the Fulfiller/Employee agents together, wants a guided Agentforce ITSM walkthrough, or asks what Agentforce features are available for IT Service. Presents available Agentforce capabilities and delegates each selection to a specialized child skill while tracking progress. Triggers on: set up agentforce for itsm, configure agentforce studio and fulfiller, agentforce itsm walkthrough, what agentforce features for it service. DO NOT TRIGGER when: the user asks to enable Agentforce Studio alone, asks to create or activate the Fulfiller or Employee agent alone, or asks about CMDB, Incident Management, Teams, or general ITSM setup without Agentforce intent.
Token-efficient web browsing and web content extraction for AI agents. Use when reading a URL, browsing websites, checking links, extracting static page content, or replacing raw HTML and browser screenshots.
Infrastructure deployment for web novel writing toolset. Provides built-in adapters for Claude Code / OpenCode / Codex / ZCode / OpenClaw / Reasonix; Web AI / general Agents can adopt the skills + AGENTS.md file mode. Trigger methods: /story-setup, $story-setup, "Prepare to write a book", "Help me set up the environment", "Configure writing project"
Multi-perspective adversarial review. Full/lean modes spawn in parallel when reviewer agents are deployed; automatically degrade to solo mode when agents are missing/abnormal or spawn fails; use built-in rubric fallback when reference files are unreadable. Trigger methods: /story-review, /审查, "审查一下", "帮我审一下"
Routes explicitly requested agent collaboration across direct work, focused headless Grok delegation, Pi subagents, and Herdr. Use when the user asks to delegate, coordinate agents, run parallel reviewers or researchers, use Herdr or Pi subagents, or choose a collaboration backend. Do not use for ordinary single-agent tasks.
Run a multi-lens agent QA sweep of the RUNNING product: spawn `qa` agents (one per lens — user-flow · edge-state · honesty · contract · ux-critique), collect their structured findings, integrator-verify the load-bearing ones, and land verified findings as backlog tickets + a run record in the project's qa/ folder. Use whenever the user asks to QA, test, or probe the product from the user's side — "qa sweep", "test the UI", "walk the flows", "find inconsistencies", "check how this looks to a client" — and proactively after integrating any large UI slice, before a milestone, or when a manual walk found one bug and siblings are likely. Trigger even when the user names only one angle (e.g. "check the API errors") — pick the matching lens subset. NOT for unit testing (your test suite does that) and NOT a replacement for the integrator's own acceptance walk.
Guide the ZenML Pro hosted Kitaru onboarding tour from preloaded traces through human review, one reusable evaluator, and one bounded replay. Use only inside the controlled hosted onboarding runner. Resume exact durable workspace state, handle existing agents without name collisions, and keep the tour concise.