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Found 6,487 Skills
Loads documents fully into the main agent's context so the agent can answer questions, summarize, or work with that content in subsequent turns. Use whenever the user wants to ingest, read, study, review, absorb, or pull in documents — especially when they say things like "load these docs", "read all of these", "ingest this folder", "pull in these PDFs", "load all docs in X", or paste a list of file paths/URLs and ask you to read them. Handles local files (text, code, markdown, PDFs, notebooks, images), entire folders (recursively), and remote URLs. The skill is single-turn — once the agent reports "DONE", it deactivates until the user invokes it again.
Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what agentmemory can do via MCP.
Run a spec-driven agent loop where coding tasks live as markdown specs that move through inbox → active → archive, get implemented by Claude Code or Codex, and pass a review gate before they count as done. Use when the user mentions "loop factory", a "spec-driven loop", an "agent factory", wants repeatable/reviewable agent work, or when a repo has a factory/specs/inbox or factory/specs/active directory. Also covers installing and scaffolding the loop-factory CLI into a project.
Data Cloud 360° view of a single Agentforce session. TRIGGER when user asks to trace, inspect, summarize, or describe a specific Agentforce session by session id (Agent Session UUID `019d…` or MessagingSession id `0Mw…`). Also triggers on session discovery — find/list/search sessions by time, agent, channel, outcome, or conversation text — when the user has no session id yet. DO NOT TRIGGER for design-time architecture questions (use agentforce-architecture-analyze instead) or for runtime perf/latency/SLO questions that require platform telemetry beyond Data Cloud.
Declared architecture snapshot for one Agentforce agent: planner, topics, actions, flows, Apex, prompt templates, and NGA plugins. Renders a human-readable architecture document and Mermaid invocation graph from design-time metadata (not runtime audit rows). TRIGGER when user asks to describe, diagram, inventory, audit, document, or diff (e.g. v3 vs v5) the architecture / action tree / topic structure / tool inventory of a specific agent by agent API name in a specific org. DO NOT TRIGGER for runtime session traces, conversation transcripts, generation timings, or gateway audit chains — this skill reads design-time metadata only (use agentforce-d360-analyze for session traces).
Fetch agentic setup prompt categories from a connected Salesforce org using the Connect API. Use this skill to call GET /agenticsetup/categories and return the list of prompt categories, optionally with their nested prompts. TRIGGER when: user asks to get, fetch, list, or show agentic setup categories, prompt categories, setup copilot categories, prompt library categories, available setup prompts, Agentforce prompt library, or copilot prompts. DO NOT TRIGGER when: user wants to create new categories, work with non-categories endpoints, or generate OpenAPI specs.
Set up a lightweight Google Alerts-style coverage tracker for any number of keywords. Creates a tracker config with each keyword and what it actually means, then hands recurrence to the user's agent harness.
Audit whether a repo's docs actually ANSWER the questions a reader has — by spawning fresh, cheap (Haiku) agents that cold-read ONLY the docs and measuring how fast they reach the answer, whether they hit dead-ends, whether they fall back to source code, and whether they cite docs that contradict each other. Use after a doc reorg, when docs "feel scattered," or when the same confusion keeps recurring. Surfaces findability gaps (a corpus can be COMPLETE — every doc indexed — yet not FINDABLE) plus a prioritized fix list. Works on any repo's docs, not just this one.
Integrate and operate BOUND, the deterministic bounded-utility control policy for agent workflows. Use when an agent must install bound-policy, define StepContracts, collect real ExecutionEvidence, evaluate meaningful execution boundaries, react to ACCEPT/RETRY/REPLAN/ROLLBACK, audit an existing BOUND integration, or produce a reproducible numeric integration report.
Use this skill to Upgrade Einstein Bots into Agentforce agents end-to-end in a single pass, orchestrating per-bot Agent Spec generation, planner reconciliation across bots, agentforce-generate authoring, and post-conversion .agent enhancements. TRIGGER when: user asks to migrate, upgrade, or convert one or more Einstein Bots to Agentforce; runs a multi-bot bot-to-agent upgrade; needs Einstein Bot metadata turned into Agent Spec handoffs and generated .agent agents; convert bots to agents; upgrade my service bots; move bots to Agentforce. DO NOT TRIGGER when: user already has an approved Agent Spec and only wants direct .agent authoring, deploy, test, or observe flows; the request is unrelated to Einstein Bot migration.
Design and build LLM-powered projects from ideation through deployment. Use when starting new agent projects, choosing between LLM and traditional approaches, or structuring batch processing pipelines.
Build AI applications with OpenAI Agents SDK - text agents, voice agents, multi-agent handoffs, tools with Zod schemas, guardrails, and streaming. Prevents 11 documented errors. Use when: building agents with tools, voice agents with WebRTC, multi-agent workflows, or troubleshooting MaxTurnsExceededError, tool call failures, reasoning defaults, JSON output leaks.