# Warlock AI

> Package: `@warlock.js/ai`

> Core @warlock.js AI framework — contracts, agent, workflow, supervisor

## Skills

- [ai-basics](@warlock.js/ai/ai-basics/SKILL.md): Start with @warlock.js/ai — provider-agnostic core for agents / tools / workflows / supervisors / orchestrators. 4-primitive ladder (agent → workflow → supervisor → orchestrator, all shipped) plus planner, memory, stores, DX helpers, and the optional @warlock.js/ai-panoptic observability sidecar. Every primitive returns {data, error, usage, report}. Triggers: `ai.agent`, `ai.tool`, `ai.workflow`, `ai.supervisor`, `ai.orchestrator`, `ai.planner`, `ai.memory`, `ai.systemPrompt`, `ExecuteResult`, `BaseReport`, `AIError`, `panoptic`; 'which AI primitive do I use', 'what is warlock ai', 'pick an AI skill', 'how do I observe / trace AI runs'; typical import `import { ai } from "@warlock.js/ai"`. Skip: agent details — `@warlock.js/ai/run-ai-agent/SKILL.md`; competing libs `langchain`, `llamaindex`, `ai` (Vercel SDK); raw `openai` / `@anthropic-ai/sdk`.
- [ai-dx-helpers](@warlock.js/ai/ai-dx-helpers/SKILL.md): Developer-experience helpers across @warlock.js/ai — ai.batch (fan-out an executable over a dataset w/ concurrency + per-item retry), ai.fallbackModel (ordered model failover), agent.eval + ai.eval scorers + Vitest matchers (registerAiMatchers / toRouteTo / toConverge / toPassStep / toOutputShape) + ai.mockRouter, SLO/cost budget contracts (ai.middleware.budget({contract}) + readBudgetFallbackSignal), supervisor-level middleware, ai.systemPrompt.fromFile, and auto-adapt executables in tools:[]. Triggers: `ai.batch`, `BatchResult`, `ai.fallbackModel`, `FallbackModelContract`, `agent.eval`, `ai.eval`, `EvalReport`, `EvalScorer`, `ai.eval.judge`, `registerAiMatchers`, `toRouteTo`, `toConverge`, `toPassStep`, `toOutputShape`, `ai.mockRouter`, `MockSDK`, `mockAgent`, `budget({contract})`, `BudgetContract`, `maxLatencyMs`, `onViolation`, `readBudgetFallbackSignal`, `supervisor middleware`, `systemPrompt.fromFile`; 'run an agent over a list', 'fail over to a backup model', 'evaluate / score an agent', 'SLO budget', 'test a supervisor without an LLM', 'prompt from a file'; typical import `import { ai } from "@warlock.js/ai"`. Skip: core agent lifecycle — `@warlock.js/ai/run-ai-agent/SKILL.md`; the budget/guardrail/semanticCache basics — `@warlock.js/ai/attach-ai-middleware/SKILL.md`; competing libs `promptfoo`, `langsmith`.
- [approve-tool-calls](@warlock.js/ai/approve-tool-calls/SKILL.md): Gate an agent's tool calls behind a human with `ai.human.approval(options)` (the `tool.before` approval-gate middleware) — ships in @warlock.js/ai core. Triggers: `ai.human.approval`, `humanApproval`, `HumanApprovalOptions`, `ApprovalRequest`, `ApprovalDecision`, `ApprovalHandler`, `InterruptPolicy`, `evaluatePolicy`, `ApprovalRejectedError`, `policy: { type: "allowlist" | "denylist" | "predicate" }`, decision `{ type: "approve" | "reject" | "edit" }`; 'human in the loop', 'approve a tool call before it runs', 'ask a human before the agent sends/charges/deletes', 'pause before a dangerous tool', 'let an operator edit the tool args', 'reject a tool call with a reason the model can self-correct from'. Typical import `import { ai } from "@warlock.js/ai"`. Skip: persisting the request and resuming hours later out-of-process — `@warlock.js/ai/durable-resume/SKILL.md`; the agent/middleware/tool primitives themselves — `@warlock.js/ai`.
- [attach-ai-middleware](@warlock.js/ai/attach-ai-middleware/SKILL.md): Wire agent middleware — ai.middleware.budget (token / USD caps + SLO/cost contract w/ maxLatencyMs + onViolation fallback), ai.middleware.guardrail (pre / post content checks), ai.middleware.semanticCache (exact + vector cache), supervisor-level middleware, plus authoring custom hooks (execute / trip / tool). Triggers: `ai.middleware.budget`, `ai.middleware.guardrail`, `ai.middleware.semanticCache`, `ai.middleware.compose`, `ai.middleware.forTool`, `AgentMiddleware`, `BudgetExceededError`, `GuardrailViolationError`, `BudgetContract`, `maxLatencyMs`, `onViolation`, `readBudgetFallbackSignal`, `supervisor middleware`, `SemanticCacheOptions`, `SemanticCacheScope`; 'cap token cost', 'SLO budget', 'block pii in prompts', 'semantic cache before LLM', 'supervisor-level middleware', 'write custom hook', 'isolate semantic cache per session/tenant'; typical import `import { ai } from "@warlock.js/ai"`. Skip: agent lifecycle — `@warlock.js/ai/run-ai-agent/SKILL.md`; cache drivers — `@warlock.js/ai/persist-ai-data/SKILL.md`; competing libs `langchain` callbacks.
- [define-ai-tool](@warlock.js/ai/define-ai-tool/SKILL.md): Define tools with ai.tool({...}) — typed validated async functions the model can call. Covers name / description / action / mode (feedback / silent) / input / execute, `ctx.artifacts` side-channel, `ToolExecutionError`. Triggers: `ai.tool`, `ToolContract`, `ToolContext`, `ToolCall`, `ToolExecutionError`, `artifactsSchema`, `mode: "silent"`, `workflow.asTool`; 'define a tool', 'wire tool into agent', 'tool input validation', 'side-channel artifacts'; typical import `import { ai } from "@warlock.js/ai"`. Skip: agent loop — `@warlock.js/ai/run-ai-agent/SKILL.md`; supervisor artifacts — `@warlock.js/ai/run-supervisor/SKILL.md`; competing libs `langchain` tools, raw `openai` function-calling.
- [detect-and-redact-pii](@warlock.js/ai/detect-and-redact-pii/SKILL.md): Detect and redact PII (and run model-graded moderation) with @warlock.js/ai-guard detectors — `ai.guardrail.pii(...)` and the optional `ai.guardrail.moderation(...)` peer. Triggers: `ai.guardrail.pii`, `piiDetector`, `PiiDetectorOptions`, `PiiCategory`, `mask`, `{label}`, `dictionary`, `onMatch`, `ai.guardrail.moderation`, `openAiModeration`, `OpenAiModerationOptions`, `blockOn`, `omni-moderation-latest`; 'redact PII from model output', 'mask SSN / credit card / email / phone / IP', 'stop PII leaking into a tool call', 'scrub sensitive data', 'add OpenAI moderation', 'block violent / self-harm content'; typical import `import "@warlock.js/ai-guard"` (registers `ai.guardrail.pii` / `.moderation`) or `import { pii, moderation } from "@warlock.js/ai-guard"`. Skip: composing the guard / wiring it into an agent — `@warlock.js/ai-guard/guard-input-output/SKILL.md`; routing a block to a human — `@warlock.js/ai-guard/escalate-block-to-human/SKILL.md`.
- [durable-agent-runs](@warlock.js/ai/durable-agent-runs/SKILL.md): Mid-run crash-resume for agents AND planners — opt in with durable: { store, deleteOnComplete? } on the config, pass a stable runId to execute(), and call agent.resume(runId) / planner.resume(runId) after a crash to continue from the last settled trip / plan node. Reuses the ai.snapshot.{memory,pg,redis} stores; checkpoints per-trip (agent) / per-node (planner); completed trips + nodes never re-run their tools and usage is never double-counted; a drifted definition throws AgentDriftError / PlannerDriftError (bypass with { force: true }). Triggers: `durable`, `agent.resume`, `planner.resume`, `resume(runId)`, `runId`, `AgentSnapshot`, `PlannerSnapshot`, `AgentSnapshotStatus`, `PlannerSnapshotStatus`, `AgentDriftError`, `PlannerDriftError`, `computeAgentSignature`, `agent.signature`, `deleteOnComplete`, `defaultSnapshotStore`, `ai.snapshot.pg`, `ai.snapshot.memory`, `SnapshotStore`, `force: true`; 'resume an agent after a crash', 'durable agent run', 'continue a planner from where it crashed', 'checkpoint agent state', 'idempotent tool re-run on resume', 'signature drift on resume'; typical import `import { ai } from "@warlock.js/ai"`. Skip: durable human-in-the-loop approval resume (ai.human.resume of a PendingInterrupt) — `@warlock.js/ai/durable-resume/SKILL.md`; supervisor/workflow iterate-mid-turn snapshot resume + the store contracts themselves — `@warlock.js/ai/manage-ai-stores/SKILL.md`; competing libs `temporal`, `inngest`, `restate`.
- [durable-resume](@warlock.js/ai/durable-resume/SKILL.md): Persist a gated tool call and resume it from another process hours later — ships in @warlock.js/ai core: `ai.human.resume(interruptId, decision, options)`, the `InterruptStore` (`ai.human.interrupt.{memory,pg,redis}()`), `PendingInterrupt`, and the `InterruptSuspendedError` suspend sentinel. Triggers: `ai.human.resume`, `resume(interruptId, decision)`, `InterruptStore`, `ai.human.interrupt.memory`, `ai.human.interrupt.pg`, `ai.human.interrupt.redis`, `interruptMemory`, `interruptPg`, `interruptRedis`, `PendingInterrupt`, `InterruptSuspendedError`, `ResumeOptions`, `ResumeResult`, `PgClientLike`, `RedisClientLike`; 'approve hours later from a webhook', 'persist the approval request and resume in another process', 'durable human-in-the-loop', 'store the interrupt in Postgres/Redis', 're-run the agent turn once the human approves'. Typical import `import { ai, InterruptSuspendedError } from "@warlock.js/ai"`. Skip: the in-process await gate and the policy/decision shapes — `@warlock.js/ai/approve-tool-calls/SKILL.md`.
- [embed-text](@warlock.js/ai/embed-text/SKILL.md): Text-to-vector via sdk.embedder({...}) — embed(string) for single, embedMany(string[]) for batch. Peer primitive on the SDK adapter, not wired into agents. Compose into RAG tools, workflow run steps, or ai.middleware.semanticCache. Triggers: `sdk.embedder`, `EmbedderContract`, `embedder.embed`, `embedder.embedMany`, `EmbeddingResult`, `EmbeddingBatchResult`, `dimensions`; 'embed text', 'build RAG tool', 'populate vector store', 'embedding batch'; typical import `import { OpenAISDK } from "@warlock.js/ai-openai"`. Skip: cache similarity — `@warlock.js/cache/use-cache-similarity/SKILL.md`; pgvector queries — `@warlock.js/cascade/search-by-vector/SKILL.md`; competing libs `langchain` embeddings, raw `openai.embeddings.create`.
- [escalate-block-to-human](@warlock.js/ai/escalate-block-to-human/SKILL.md): Route a hard guardrail block to a human-review surface with @warlock.js/ai-guard — the `escalation.onBlock` seam and an `escalate: true` verdict. Triggers: `escalation`, `onBlock`, `GuardrailEscalation`, `GuardrailBlockEvent`, `escalate: true`, `{ type: "block", escalate: true }`, 'escalate a block to a human', 'human review queue for guardrail', 'page an operator on a guardrail block', 'human-in-the-loop guardrail', 'compose a block with a review surface', 'custom detector that escalates'; typical import `import "@warlock.js/ai-guard"` then `ai.guardrail({ escalation: { onBlock } })`. Skip: composing the guard / phases / verdict model — `@warlock.js/ai-guard/guard-input-output/SKILL.md`; PII/moderation detectors — `@warlock.js/ai-guard/detect-and-redact-pii/SKILL.md`; durable suspend/resume human-step machinery (deferred) — not in this package.
- [eval-datasets-and-ci](@warlock.js/ai/eval-datasets-and-ci/SKILL.md): Datasets + regression-gated eval CI with ai.dataset({...}) feeding agent.eval({cases,baseline,tolerance}). Covers the immutable filterable/shardable dataset (cases / fromFile JSONL), DatasetEntry tags, EvalReport.regression (regressed/added/removed/passed) against a baseline, and the ai.eval reporters toJUnit / toJSON / fromJSON for CI artifacts + committed baselines. Triggers: `ai.dataset`, `DatasetContract`, `DatasetEntry`, `DatasetOptions`, `dataset.filter`, `dataset.shard`, `fromFile`, `agent.eval`, `EvalOptions`, `EvalReport`, `EvalCaseResult`, `EvalRegression`, `baseline`, `tolerance`, `ai.eval.toJUnit`, `ai.eval.toJSON`, `ai.eval.fromJSON`, `diff`, JSONL; 'eval dataset from a JSONL file', 'shard an eval suite across CI jobs', 'fail CI on an eval regression', 'emit a JUnit report', 'snapshot an eval baseline'; typical import `import { ai } from "@warlock.js/ai"`. Skip: the scorers + LLM-as-judge + Vitest matchers themselves — `@warlock.js/ai/ai-dx-helpers/SKILL.md` (registerAiMatchers / ai.eval.exact|contains|predicate|judge); record/replay of model calls for deterministic tests — `@warlock.js/ai/record-replay-llm/SKILL.md`; competing libs `promptfoo`, `braintrust`.
- [generate-images](@warlock.js/ai/generate-images/SKILL.md): Text-to-image via ai.image({ model: sdk.image({ name }), prompt }) — the image-OUTPUT verb (Theme I), returning the uniform never-throws { data, error, usage, report } envelope with cost-truth + panoptic observation. Models come from an adapter's image() factory: OpenAI gpt-image-* (token-metered) / dall-e-* (per-image), Google gemini-* (generateContent + responseModalities IMAGE, usage passed through) / imagen-* and every other id (per-image, generateImages — deprecated by Google); the id picks the transport and is never validated locally. Result images are a discriminated GeneratedImage = { type: "base64" } | { type: "url" }. Triggers: `ai.image`, `sdk.image`, `openai.image`, `google.image`, `ImageModelContract`, `GeneratedImage`, `ImageModelPricing`; 'generate an image', 'text to image', 'gpt-image', 'dall-e', 'imagen', 'product thumbnail', 'image output'; typical import `import { ai } from "@warlock.js/ai"` + `import { OpenAISDK } from "@warlock.js/ai-openai"`. Skip: image INPUT / vision attachments to a chat agent — `@warlock.js/ai/run-ai-agent/SKILL.md`; embeddings — `@warlock.js/ai/embed-text/SKILL.md`; competing libs raw `openai.images.generate`, `langchain` image tools.
- [generate-speech](@warlock.js/ai/generate-speech/SKILL.md): Text-to-speech via ai.speech({ model: sdk.speech({ name }), text }) — the audio-OUTPUT verb (Theme I), returning the uniform never-throws { data, error, usage, report } envelope with cost-truth + panoptic observation. Models come from an adapter's speech() factory: OpenAI tts-1 / tts-1-hd (per-character) or gpt-4o-mini-tts (per-token). Synthesized audio is a discriminated GeneratedAudio = { type: "base64"; base64; mediaType }. Options: voice / format / speed / instructions / signal. Triggers: `ai.speech`, `sdk.speech`, `openai.speech`, `SpeechModelContract`, `GeneratedAudio`, `SpeechModelPricing`, `SpeechOptions`, `MockSpeechModel`; 'text to speech', 'TTS', 'synthesize voice', 'read this aloud', 'tts-1', 'gpt-4o-mini-tts', 'voice narration', 'audio output', 'speak this text'; typical import `import { ai } from "@warlock.js/ai"` + `import { OpenAISDK } from "@warlock.js/ai-openai"`. Skip: speech-to-text / transcribing a voice note — [[transcribe-audio]]; image OUTPUT — [[generate-images]]; competing libs raw `openai.audio.speech.create`, `elevenlabs` SDK.
- [guard-input-output](@warlock.js/ai/guard-input-output/SKILL.md): Build the composed guardrail middleware with @warlock.js/ai-guard and wire it into an agent — `ai.guardrail({ input, output, tool, toolNames, escalation })`. Triggers: `ai.guardrail`, `guard`, `GuardOptions`, `GuardrailVerdict`, `GuardrailDetector`, `GuardrailPhase`, `GuardrailMatch`, `GuardrailViolationError`, `ai.guardrail.topic`, `ai.guardrail.injection`, `topicFilter`, `injectionDetector`, `toolNames`, `forTool`; 'add a guardrail to my agent', 'block prompt injection', 'filter banned topics', 'guard agent input and output', 'stop the model leaking data into a tool call', 'scope a detector to one tool'; typical import `import "@warlock.js/ai-guard"` (registers `ai.guardrail`) or `import { guard } from "@warlock.js/ai-guard"`. Skip: PII detection/redaction specifically — `@warlock.js/ai-guard/detect-and-redact-pii/SKILL.md`; routing a block to a human — `@warlock.js/ai-guard/escalate-block-to-human/SKILL.md`; the core middleware pipeline / hook contract — `@warlock.js/ai/run-ai-agent/SKILL.md`.
- [handle-ai-errors](@warlock.js/ai/handle-ai-errors/SKILL.md): Typed AIError hierarchy with stable code strings + coarse category for retry-policy dispatch. execute() never throws — errors surface via result.error (the sole exception: OrchestratorConfigError throws at construction). Triggers: `AIError`, `ProviderRateLimitError`, `ProviderAuthError`, `ContextLengthExceededError`, `ContentFilterError`, `SchemaValidationError`, `ToolExecutionError`, `WorkflowDriftError`, `SupervisorDriftError`, `SupervisorFailedError`, `SupervisorRoutingError`, `OrchestratorFailedError`, `OrchestratorDriftError`, `OrchestratorConfigError`, `OrchestratorCancelledError`, `PlannerFailedError`, `PlannerPlanInvalidError`, `PlannerCancelledError`, `BudgetExceededError`, `GuardrailViolationError`, `error.code`, `error.category`; 'handle ai error', 'retry on rate limit', 'branch on error code', 'ORCHESTRATOR_DRIFT', 'PLANNER_PLAN_INVALID', 'build fallback ladder'; typical import `import { AIError } from "@warlock.js/ai"`. Skip: log surfacing — `@warlock.js/ai/log-ai-calls/SKILL.md`; native `try / catch` on raw `openai`.
- [log-ai-calls](@warlock.js/ai/log-ai-calls/SKILL.md): Framework logging delegated to @warlock.js/logger — every primitive emits via the log singleton, configure channels / levels / redaction once at boot. Four-arg call convention (module, action, message, context). Triggers: `log.configure`, `log.setMinLevel`, `log.setChannels`, `ConsoleLog`, `FileLog`, `LogChannel`, `redact.paths`, `ai.agent.<name>` / `ai.workflow.<name>` / `ai.supervisor.<name>` modules; 'configure ai logging', 'mask prompts in logs', 'silence logs in tests', 'capture log entries'; typical import `import { log } from "@warlock.js/logger"`. Skip: error hierarchy — `@warlock.js/ai/handle-ai-errors/SKILL.md`; competing libs `pino`, `winston`, `console.log`.
- [manage-ai-stores](@warlock.js/ai/manage-ai-stores/SKILL.md): Durable orchestrator stores — ai.checkpoint.{memory,pg,redis}() for cross-turn SESSION STATE and ai.snapshot.{memory,pg,redis}() for in-flight SUPERVISOR/WORKFLOW run state. Two distinct contracts (CheckpointStore vs SnapshotStore), dev-owned pg/redis clients (no peer dep), never-auto-migrated schema(), global defaults via ai.config({defaultCheckpointStore, defaultSnapshotStore}). Triggers: `ai.checkpoint`, `ai.snapshot`, `checkpointStore`, `snapshotStore`, `CheckpointStore`, `SnapshotStore`, `CheckpointRecord`, `checkpoint.pg`, `checkpoint.redis`, `snapshot.pg`, `snapshot.redis`, `store.schema()`, `keepSnapshots`, `defaultCheckpointStore`, `defaultSnapshotStore`, `PgClientLike`, `RedisClientLike`; 'persist orchestrator sessions', 'wire a pg checkpoint store', 'run the store DDL', 'checkpoint vs snapshot'; typical import `import { ai } from "@warlock.js/ai"`. Skip: orchestrator lifecycle — `@warlock.js/ai/run-orchestrator/SKILL.md`; cache-backed snapshot resume / semanticCache store — `@warlock.js/ai/persist-ai-data/SKILL.md`; competing libs `temporal`, `inngest`.
- [manage-prompts](@warlock.js/ai/manage-prompts/SKILL.md): Unified prompt registry — ai.prompts: one process-wide store of named, versioned systemPrompt(...) builders keyed by name@version. Register by giving a prompt a meta.name (auto-registers), resolve by get(name) / resolve(name, versionOrTag, placeholders) / the inline name@selector form, bulk-register with define(name, versions), pin tags with tag(name, tag, version), compare with diff(name, from, to), round-trip with export() / import(snapshot), and quality-check with a unified validate(target, options) (deterministic missing-placeholder check + optional Nova-safe LLM-as-judge with verdict caching). Compose registered prompts into new ones with systemPrompt().merge(name, { fromVersion }) — provenance recorded in meta.composedFrom. ai.prompt is now a thin FACADE over ai.prompts (BREAKING vs the old standalone registry). Triggers: `ai.prompts`, `ai.prompt`, `PromptsManagerContract`, `PromptsManagerEntry`, `SystemPromptContract`, `SystemPromptMeta`, `SystemPromptMergeOptions`, `PromptsValidateOptions`, `PromptValidationResult`, `PromptValidateTarget`, `PromptTemplateVersion`, `PromptDiff`, `ExportedRegistry`, `defaultPromptsManager`, `prompts()`, `promptKey`, `meta`, `name`, `version`, `composedFrom`, `fromVersion`, `register`, `create`, `get`, `has`, `list`, `versions`, `resolve`, `define`, `tag`, `validate`, `diff`, `export`, `import`, `merge`, `judge`, `judgeCache`, `criteria`; 'register a prompt by name', 'resolve a prompt by name@version or tag', 'pin a production tag to a prompt version', 'diff two prompt versions', 'export / import the prompt registry', 'validate a prompt for missing placeholders', 'validate a prompt against my own criteria / rules', 'merge a registered prompt into another'; typical import `import { ai } from "@warlock.js/ai"`. Skip: composing a single prompt from persona + instruction blocks (the builder itself) — `@warlock.js/ai/write-system-prompt/SKILL.md`; runtime loadable skill bodies — `@warlock.js/ai/use-runtime-skills/SKILL.md`; eval scoring of agent outputs — `@warlock.js/ai/eval-datasets-and-ci/SKILL.md`; competing libs `langfuse` (direct), `promptfoo`.
- [observe-ai-flows](@warlock.js/ai/observe-ai-flows/SKILL.md): The core Observer seam — a generic, tool-agnostic observability hook every flow routes its completed ExecutionReport through. Covers the per-flow `observe?: boolean | Observer` option on ai.agent / workflow / supervisor / team, the global registry (registerObserver / getObservers / setObserveAll / isObserveAll / clearObservers), resolveObservers / notifyObservers resolution, the opt-in AgentConfig.captureMessages → AgentReport.messages full-history capture, the onConfigApplied dependency-inversion seam, and that @warlock.js/ai-panoptic is the batteries-included Observer. Triggers: `Observer`, `observe`, `registerObserver`, `getObservers`, `setObserveAll`, `isObserveAll`, `clearObservers`, `resolveObservers`, `notifyObservers`, `FlowObserveOption`, `ExecutionReport`, `captureMessages`, `AgentReport.messages`, `CapturedMessage`, `onConfigApplied`, `observeAll`; 'observe an agent run', 'send finished reports to a collector', 'capture the full message history', 'observe every flow by default', 'wire panoptic / tracing'; typical import `import { ai, registerObserver } from "@warlock.js/ai"`. Skip: structured logging of events — `@warlock.js/ai/log-ai-calls/SKILL.md`; reading the report tree shape (trips / children) — `@warlock.js/ai/run-ai-agent/SKILL.md`; per-call cost / usage rollup — `@warlock.js/ai/handle-ai-errors/SKILL.md`. The batteries-included Observer is the `@warlock.js/ai-panoptic` package.
- [persist-ai-data](@warlock.js/ai/persist-ai-data/SKILL.md): Persistence delegated to @warlock.js/cache — workflow + supervisor snapshot resume via snapshotStore (4.3.0: now a SnapshotStore from ai.snapshot.*, ⚠ moved off raw CacheDriver), semantic cache + memory via vector-capable CacheDriver, global defaults via ai.config({defaultStore}) + ai.config({defaultSnapshotStore}). Covers drift detection + three recovery paths. Triggers: `ai.config`, `defaultStore`, `defaultSnapshotStore`, `snapshotStore`, `ai.snapshot`, `wf.resume`, `supervisor.resume`, `WorkflowSnapshot`, `SupervisorSnapshot`, `WorkflowDriftError`, `SupervisorDriftError`, `force: true`; 'resume a workflow run', 'configure snapshot store', 'handle signature drift', 'wire pg vector cache'; typical import `import { ai } from "@warlock.js/ai"`. Skip: orchestrator checkpoint/snapshot store factories — `@warlock.js/ai/manage-ai-stores/SKILL.md`; cache driver catalog — `@warlock.js/cache/cache-basics/SKILL.md`; competing libs `temporal`, `inngest`.
- [pick-ai-provider](@warlock.js/ai/pick-ai-provider/SKILL.md): Choose an AI provider adapter — @warlock.js/ai-openai (shipped, also handles OpenRouter / Azure via baseURL), @warlock.js/ai-anthropic, @warlock.js/ai-bedrock, @warlock.js/ai-google, @warlock.js/ai-ollama — plus cost truth: ModelPricing (per-1M tokens), Usage cost breakdown, the cachedTokens / cacheWriteTokens / reasoningTokens channels, and capability flags. Triggers: `OpenAISDK`, `SDKAdapterContract`, `ModelContract`, `ModelPricing`, `ModelCapabilities`, `sdk.model`, `sdk.embedder`, `capabilities.vision`, `capabilities.structuredOutput`, `capabilities.reasoning`, `capabilities.promptCaching`, `pricing`, `Usage.cost`, `cachedTokens`, `cacheWriteTokens`, `reasoningTokens`, `reasoning.effort`, `cacheControl`, `baseURL`, `provider: "openrouter"`; 'pick a provider', 'openai vs openrouter', 'does this model support vision/reasoning', 'configure pricing', 'how much did reasoning cost', 'prompt cache tokens'; typical import `import { OpenAISDK } from "@warlock.js/ai-openai"`. Skip: agent factory — `@warlock.js/ai/run-ai-agent/SKILL.md`; competing libs raw `openai`, `@anthropic-ai/sdk`, `@aws-sdk/client-bedrock-runtime`.
- [rag-loaders-and-stores](@warlock.js/ai/rag-loaders-and-stores/SKILL.md): Turn any source into a RagDocument and index it in a production vector store — the document loaders ai.rag.loadText / loadHtml / loadWeb (SSRF-safe via guardedFetch) / loadPdf (lazy pdf-parse peer), plus the swappable stores ai.rag.pgVectorStore({client}) (pgvector + ensureSchema DDL + hnsw/ivfflat index) and ai.rag.cacheVectorStore(driver), both satisfying VectorStoreContract (upsert / query / removeNamespace). Loaders return the exact RagDocument[] that kb.index() consumes — no adapter. Triggers: `ai.rag.loadText`, `ai.rag.loadHtml`, `ai.rag.loadWeb`, `ai.rag.loadPdf`, `loadText`, `loadHtml`, `loadWeb`, `loadPdf`, `ai.rag.pgVectorStore`, `ai.rag.cacheVectorStore`, `pgVectorStore`, `cacheVectorStore`, `VectorStore`, `PgVectorStoreOptions`, `PgVectorStoreInstance`, `ensureSchema`, `schema()`, `RagLoaderResult`, `LoadWebOptions`, `LoadPdfOptions`, `perPage`, `OutboundPolicy`, `guardedFetch`, `hnsw`, `ivfflat`, `pgvector`, `dimensions`, `PgClientLike`, `PDF_PARSE_INSTALL_INSTRUCTIONS`; 'load a website into a knowledge base', 'index a PDF for RAG', 'strip HTML to text for embedding', 'pgvector store for RAG', 'SSRF-safe document fetch', 'one document per PDF page', 'swap the vector store'; typical import `import { ai } from "@warlock.js/ai"`. Skip: the chunk → embed → retrieve → rerank → cite pipeline that consumes these — `@warlock.js/ai/run-ai-rag/SKILL.md`; the raw embedder primitive — `@warlock.js/ai/embed-text/SKILL.md`; cache similarity internals — `@warlock.js/cache/use-cache-similarity/SKILL.md`; competing libs `langchain` loaders, `llamaindex` readers.
- [record-replay-llm](@warlock.js/ai/record-replay-llm/SKILL.md): Deterministic, offline LLM tests with ai.vcr(model,{path,mode}) — a record/replay decorator over ANY ModelContract that intercepts only complete()/stream(), delegates name/provider/capabilities/pricing to the inner model, and hashes each request against a JSON cassette on disk. Covers the three modes (record / replay / auto), the cassette format, save(), VcrCassetteMissError, streaming round-trip, hashOptions, and composing below fallbackModel. Triggers: `ai.vcr`, `vcr`, `VcrModel`, `VcrOptions`, `VcrMode`, `Cassette`, `CassetteEntry`, `VcrCassetteMissError`, `hashRequest`, `DEFAULT_HASH_OPTIONS`, `mode`, `path`, `hashOptions`, `save`, `cassette`, record, replay, cassette; 'record LLM responses for tests', 'replay model calls offline in CI', 'deterministic agent test without hitting the provider', 'cassette for model calls'; typical import `import { ai } from "@warlock.js/ai"`. Skip: eval scoring + regression gating — `@warlock.js/ai/eval-datasets-and-ci/SKILL.md`; the Vitest matchers + mockRouter — `@warlock.js/ai/ai-dx-helpers/SKILL.md`; choosing a provider adapter — `@warlock.js/ai/pick-ai-provider/SKILL.md`; competing libs `nock`, `polly.js`.
- [refine-prompts](@warlock.js/ai/refine-prompts/SKILL.md): Prompt compiler — systemPrompt(...).refined({ model, criteria, store }): humans keep writing human prompt text (dev code or admin-panel textareas); the refined wrapper lazily rewrites it into a model-optimized version via a refiner model on first agent use, pins the result (lockfile posture — recompiled ONLY when the source text, refiner model, criteria, or built-in recipe version change, never silently over time), and serves the pin thereafter. Explicit surfaces: await refined.refine() → the compiled template STRING (placeholders intact — for admin routes, previews, boot warmup, CI; throws PromptRefinementError on failure) and await refined.refinePrompt() → a composable SystemPromptContract with meta.refinedFrom / meta.refinerModel provenance (register it as a next version to unlock ai.prompts.diff review). Placeholder parity is machine-enforced (the exact {{placeholder}} set must survive or the rewrite is rejected after one repair re-ask); the lazy agent path NEVER throws — on refiner failure it warns once and serves the original. store is a structural { get, set } (any @warlock.js/cache CacheDriver); omitted ⇒ the pin lives on the instance for the process lifetime. Triggers: `refined`, `refine`, `refinePrompt`, `materialize`, `RefinedSystemPromptContract`, `RefinedSystemPromptOptions`, `RefinedPromptStoreLike`, `PromptRefineOptions`, `PromptRefinementError`, `refinedFrom`, `refinerModel`, `fresh`, `prompt-refiner`, 'refine a prompt', 'compile a prompt', 'optimize a system prompt', 'rewrite my prompt to be AI-friendly', 'admin-written prompts', 'prompt refinement store'; typical import `import { ai } from "@warlock.js/ai"`. Skip: registry operations (register / resolve / tag / diff / validate) — `@warlock.js/ai/manage-prompts/SKILL.md`; composing prompts from persona + instruction blocks — `@warlock.js/ai/write-system-prompt/SKILL.md`; grading a prompt against rules without rewriting it — validate({ criteria }) in `@warlock.js/ai/manage-prompts/SKILL.md`.
- [run-ai-agent](@warlock.js/ai/run-ai-agent/SKILL.md): Build agents with ai.agent({...}) — the single-LLM-turn primitive. Covers execute / stream, attachments, structured output, placeholders, events, agent.eval scoring, the judge-safe preset for resilient LLM-as-judge / verdict classifiers (ai.agent.judge / judge: true — lenient JSON parse + repair + never-throw, for Nova-class models), and auto-adapting raw executables in tools:[]. Triggers: `ai.agent`, `ai.agent.judge`, `agent.execute`, `agent.stream`, `agent.eval`, `AgentResult`, `AgentReport`, `AgentToolEntry`, `JudgeConfig`, `JudgeAgentConfig`, `judge`, `repairAttempts`, `streamingToolGuard`, `attachments`, `repair`, `maxTrips`, `sessionId`, `spawnSubAgent`, `SpawnSubAgentSpec`; 'run an agent', 'stream an agent response', 'structured output schema', 'pass image to agent', 'evaluate an agent', 'LLM-as-judge that survives malformed JSON', 'grade with a Nova model without crashing', 'put a supervisor in tools', 'cancel an agent run', 'spawn a one-shot sub-agent with a per-task budget'; typical import `import { ai } from "@warlock.js/ai"`. Skip: tool definition — `@warlock.js/ai/define-ai-tool/SKILL.md`; workflows — `@warlock.js/ai/run-ai-workflow/SKILL.md`; eval matchers / batch / fallback detail — `@warlock.js/ai/ai-dx-helpers/SKILL.md`; competing libs `langchain`, `ai` (Vercel), raw `openai`.
- [run-ai-rag](@warlock.js/ai/run-ai-rag/SKILL.md): Retrieval-augmented generation with ai.rag({...}) — a chunk → embed → vector-store → retrieve → rerank → cite pipeline that reuses ai.embedder + a @warlock.js/cache CacheDriver. Covers index() / retrieve() / clear() / asTool(), chunking strategies (recursive | markdown | sentence | fixed), Citation / RetrievedChunk provenance, and the opt-in rerankers ai.rag.keywordReranker / ai.rag.llmReranker. Triggers: `ai.rag`, `rag.index`, `rag.retrieve`, `rag.clear`, `rag.asTool`, `RagConfig`, `RagDocument`, `RetrieveOptions`, `RetrieveResult`, `RetrievedChunk`, `Citation`, `ChunkOptions`, `ChunkType`, `ai.rag.keywordReranker`, `ai.rag.llmReranker`, `cacheVectorStore`, `VectorStore`, `topK`, `threshold`, `candidates`; 'build a knowledge base', 'retrieve relevant chunks for a query', 'cite the source of an answer', 'chunk markdown for embedding', 'rerank retrieval results', 'expose retrieval as a tool'; typical import `import { ai } from "@warlock.js/ai"`. Skip: raw single-string embedding — `@warlock.js/ai/embed-text/SKILL.md`; exact + vector LLM-response cache — `@warlock.js/ai/attach-ai-middleware/SKILL.md` (ai.middleware.semanticCache); tool wiring — `@warlock.js/ai/define-ai-tool/SKILL.md`; competing libs `langchain`, `llamaindex`.
- [run-ai-team](@warlock.js/ai/run-ai-team/SKILL.md): Manager-led multi-agent teams with ai.team({...}) — transparent sugar over ai.supervisor that maps a manager → route/router, members → intents, and a gate → evaluate, returning a REAL SupervisorContract (no new loop, no new contract). Covers the built-in gate strings "quality" (review-then-fix) and "verify" (test-then-fix), a custom gate function, role mapping (roles / gateKey), and the verbatim supervisor pass-throughs (goal / output / state / maxIterations / snapshotStore / on / observe). Triggers: `ai.team`, `TeamConfig`, `TeamGate`, `TeamGateFn`, `TeamMemberValue`, `manager`, `members`, `gate`, `roles`, `gateKey`, `buildQualityGate`, `buildVerifyGate`, `SupervisorContract`, `ReportType`; 'build a team of agents', 'manager that delegates to members', 'review then fix loop', 'test then fix loop', 'quality gate for a multi-agent run', 'report type team'; typical import `import { ai } from "@warlock.js/ai"`. Skip: routing one input to a fixed roster directly — `@warlock.js/ai/run-supervisor/SKILL.md` (team is sugar over it); durable cross-turn sessions — `@warlock.js/ai/run-orchestrator/SKILL.md`; LLM-generated plans — `@warlock.js/ai/run-planner/SKILL.md`; competing libs `crewai`, `autogen`.
- [run-ai-workflow](@warlock.js/ai/run-ai-workflow/SKILL.md): Build durable resumable pipelines with ai.workflow({...}) + ai.step({...}) — lifecycle (skip / before / run|agent|parallel / output / after / nextStep), retry, parallel groups, snapshot resume. Triggers: `ai.workflow`, `ai.step`, `wf.execute`, `wf.resume`, `WorkflowContext`, `WorkflowResult`, `StepSnapshot`, `nextStep`, `onFailure`, `WorkflowDriftError`; 'build a workflow', 'define a step', 'resume after crash', 'parallel steps', 'retry with backoff'; typical import `import { ai } from "@warlock.js/ai"`. Skip: agent — `@warlock.js/ai/run-ai-agent/SKILL.md`; supervisor — `@warlock.js/ai/run-supervisor/SKILL.md`; competing libs `temporal`, `inngest`, `bullmq`.
- [run-orchestrator](@warlock.js/ai/run-orchestrator/SKILL.md): Durable stateful sessions with ai.orchestrator({...}) — the capstone of the 4-primitive ladder. Wraps a supervisor with cross-turn session state (checkpointStore), per-turn windowing, drift detection, post-turn compaction, mid-turn resume (iterate: true + snapshotStore), per-turn memory, typed commands, asTool, and a 3-tier event model. Triggers: `ai.orchestrator`, `orchestrator.execute`, `orchestrator.resume`, `orchestrator.command`, `orchestrator.stream`, `OrchestratorConfig`, `OrchestratorResult`, `OrchestratorReport`, `OrchestratorContract`, `CheckpointStore`, `OrchestratorDriftError`, `sessionId`, `iterate`, `historyWindow`, `summarize`, `keepSnapshots`, `awaiting-input`, `turns[]`, `TurnSnapshot`, `CompactionResult`, `initialAgent`, `checkpointStore`; 'multi-turn conversation that persists', 'durable session across calls', 'resume an interrupted turn', 'compact session history', 'per-session memory'; typical import `import { ai } from "@warlock.js/ai"`. Skip: a single routing turn with no session — `@warlock.js/ai/run-supervisor/SKILL.md`; a fixed pipeline — `@warlock.js/ai/run-ai-workflow/SKILL.md`; the store factories themselves — `@warlock.js/ai/manage-ai-stores/SKILL.md`; competing libs `langgraph`, `crewai`.
- [run-planner](@warlock.js/ai/run-planner/SKILL.md): Goal-driven planning with ai.planner({...}) — an LLM GENERATES an ordered execution plan over your registered capabilities (agents / workflows / supervisors / tools), then the planner EXECUTES it, threading each step output into the next, and returns the unified {data, report, usage, error} envelope with report.type "planner". Supports DAG scheduling (dag:true + maxConcurrency off dependsOn), adaptive re-planning (replan:{maxReplans} + the onStep continue/abort/replan directive), and plan-only / approval (mode:"plan-only" → status "awaiting-approval" → approvedPlan). A plan step may delegate via ai.spawnSubAgent({...}) — a GENERAL one-shot-agent helper covered in `@warlock.js/ai/run-ai-agent/SKILL.md`; it is not planner-specific. Triggers: `ai.planner`, `planner.execute`, `spawnSubAgent`, `PlannerConfig`, `PlannerCapability`, `PlannerResult`, `PlannerReport`, `PlannerPlan`, `PlannerStep`, `PlannerStepDirective`, `PlannerPlanInvalidError`, `maxSteps`, `dag`, `maxConcurrency`, `dependsOn`, `replan`, `onStep`, `mode`, `approvedPlan`, `awaiting-approval`, `report.plan`, `report.executedSteps`, `parsedStepCeiling`; 'let the model plan the steps', 'dynamic plan from a goal', 'run independent steps in parallel', 're-plan when a step fails', 'generate a plan for approval before running it'; typical import `import { ai } from "@warlock.js/ai"`. Skip: a FIXED known pipeline — `@warlock.js/ai/run-ai-workflow/SKILL.md`; routing one input to a specialist each turn — `@warlock.js/ai/run-supervisor/SKILL.md`; a single model + tools call — `@warlock.js/ai/run-ai-agent/SKILL.md`; competing libs `langgraph`, `crewai`.
- [run-supervisor](@warlock.js/ai/run-supervisor/SKILL.md): Multi-intent routing with ai.supervisor({...}) — classifier (iter-0 dispatch), router agent OR route callback, intents as agents / workflows / callbacks, fan-out, evaluate quality loop, ack receptionist, supervisor-level middleware. A callback that calls agent.execute() directly auto-nests agent → tool under the callback span (ambient RunFrame) with usage / cost rolled up — same for team members and orchestrator turns. Triggers: `ai.supervisor`, `ai.router`, `ai.fanOut`, `supervisor.execute`, `supervisor.resume`, `intents`, `router`, `route`, `classifier`, `evaluate`, `ack`, `artifactsSchema`, `middleware`, `END`, `ctx.intents.X.execute`, `ctx.run`, `RunFrame`, `callback span`, `children`, `parentRunId`, `rootRunId`, `trace nesting`, `sub-agent`; 'route one input across specialists', 'multi-intent dispatch', 'fan-out then evaluate', 'classifier then router', 'supervisor middleware', 'self-consistency / voting', 'why is my callback agent not nested / cost is $0', 'nest a sub-agent under a callback'; typical import `import { ai } from "@warlock.js/ai"`. Skip: durable multi-turn sessions — `@warlock.js/ai/run-orchestrator/SKILL.md`; fixed pipelines — `@warlock.js/ai/run-ai-workflow/SKILL.md`; single agent — `@warlock.js/ai/run-ai-agent/SKILL.md`; competing libs `langgraph`, `crewai`.
- [secure-outbound-requests](@warlock.js/ai/secure-outbound-requests/SKILL.md): The shared SSRF / resource-exhaustion guard every server-side outbound HTTP request in the framework goes through — `guardedFetch(url, policy, init?)`, `OutboundPolicy`, `assertUrlAllowed`, `fetchTextWithPolicy`, `readTextCapped`. Scheme allowlist (https-only default), host allowlist, post-DNS private/loopback/link-local/metadata-address deny, byte cap, timeout, and (4.15.0) per-hop redirect revalidation with a `maxRedirects` cap and cross-origin credential stripping. Consumed by `ai.rag.loadWeb`, remote text attachments (`prepareAttachmentPart`), and the skills `urlSource` manifest fetch — never a raw `fetch()` on a caller-influenced URL. Triggers: `guardedFetch`, `OutboundPolicy`, `ResolvedOutboundPolicy`, `assertUrlAllowed`, `fetchTextWithPolicy`, `readTextCapped`, `resolveOutboundPolicy`, `OutboundPolicyError`, `maxRedirects`, `denyPrivateIPsAfterDNS`, `hostAllowlist`, `allowedSchemes`, `maxBytes`, `SSRF`, `redirect: "manual"`, `redirect: "error"`; 'SSRF-safe fetch', 'block a redirect into a private IP', 'fetch a URL an agent gave me', 'cap outbound response size', 'allowlist hosts for outbound requests', 'strip auth headers on a cross-origin redirect'; typical import `import { guardedFetch, assertUrlAllowed } from "@warlock.js/ai"` (also re-exported per call site). Skip: the RAG loader that wraps this for `loadWeb` — `@warlock.js/ai/rag-loaders-and-stores/SKILL.md`; the skills manifest source that wraps this for `urlSource` — `@warlock.js/ai/use-runtime-skills/SKILL.md`; prompt-injection / content guardrails (a different trust boundary) — `@warlock.js/ai/guard-input-output/SKILL.md` (ai-guard package).
- [transcribe-audio](@warlock.js/ai/transcribe-audio/SKILL.md): Speech-to-text via ai.transcribe({ model: sdk.transcribe({ name }), audio }) — the audio-INPUT verb (Theme I), returning the uniform never-throws { data, error, usage, report } envelope with cost-truth + panoptic observation. Feed it an AudioInput = { base64; mediaType; filename? } — build one with ai.audioFromFile(path) (reads disk, infers media type incl. WhatsApp .ogg/.opus) or ai.audioFromBuffer(bytes, mediaType). Models: OpenAI whisper-1 (verbose_json, per-minute, segments + durationSeconds) or gpt-4o-transcribe (json, per-token). Triggers: `ai.transcribe`, `ai.audioFromFile`, `ai.audioFromBuffer`, `sdk.transcribe`, `openai.transcribe`, `TranscriptionModelContract`, `AudioInput`, `TranscriptionSegment`, `MockTranscriptionModel`; 'speech to text', 'transcribe audio', 'voice note to text', 'WhatsApp voice message', 'whisper', 'gpt-4o-transcribe', 'subtitle segments', 'audio input'; typical import `import { ai } from "@warlock.js/ai"` + `import { OpenAISDK } from "@warlock.js/ai-openai"`. Skip: text-to-speech / synthesizing a voice — [[generate-speech]]; competing libs raw `openai.audio.transcriptions.create`, `whisper.cpp`.
- [use-ai-memory](@warlock.js/ai/use-ai-memory/SKILL.md): Agent memory with ai.memory({...}) — a provider-neutral store with FOUR tiers: WORKING (in-run scratch, recalled by recency), SEMANTIC (durable facts by cosine similarity over a @warlock.js/cache vector driver via .similar()), EPISODIC (durable events, similarity blended with recency), and PROCEDURAL (durable how-tos, similarity blended with reinforcement). remember() / recall() / clear(); wire it into ai.orchestrator({ memory }). Triggers: `ai.memory`, `memory.remember`, `memory.recall`, `memory.clear`, `MemoryContract`, `MemoryConfig`, `MemoryItem`, `RecalledMemory`, `MemoryTier`, `SemanticMemoryConfig`, `EpisodicMemoryConfig`, `ProceduralMemoryConfig`, `working`, `semantic`, `episodic`, `procedural`, `defaultTier`, `threshold`, `recencyWeight`, `halfLifeMs`, `reinforcementWeight`, `injectKey`, `maxItems`, `scope`, `RecallOptions.scope`; 'give the agent memory', 'remember user preferences', 'semantic recall', 'per-session working memory', 'episodic / event memory', 'procedural / how-to memory', 'recency-weighted recall', 'reinforce a procedure', 'cap working memory size', 'isolate memory per session/tenant'; typical import `import { ai } from "@warlock.js/ai"`. Skip: orchestrator wiring of the memory — `@warlock.js/ai/run-orchestrator/SKILL.md`; the vector cache driver itself — `@warlock.js/cache/cache-basics/SKILL.md`; embeddings primitive — `@warlock.js/ai/embed-text/SKILL.md`; competing libs `mem0`, `langchain` memory.
- [use-runtime-skills](@warlock.js/ai/use-runtime-skills/SKILL.md): Progressive-disclosure agent skills with ai.skills({...}) and the first-class `skills` option on ai.agent — an always-injected cheap metadata catalog plus an on-demand loadSkill tool, backed by directory / url / store sources. Covers inject ("all" | {select:"semantic",topK,embedder}), maxLoadsPerRun, scope tags, the MockSkillsStore, semantic preload, and the inert-by-default Phase-2 self-authoring (saveSkill + default-DENY review gate → promote). Triggers: `ai.skills`, `SkillsConfig`, `SkillsContract`, `SkillSource`, `SkillInjectMode`, `SkillRecord`, `SkillCatalogEntry`, `loadSkill`, `loadSkillTool`, `saveSkill`, `saveSkillTool`, `SkillReviewGate`, `runReviewGate`, `MockSkillsStore`, `proceduralSkillStore`, `maxLoadsPerRun`, `inject`, `scope`, `review`, the agent `skills:` option; 'give an agent loadable skills', 'progressive disclosure of instructions', 'catalog of skills the model pulls on demand', 'semantic preload of skill bodies', 'let an agent author and review a skill'; typical import `import { ai } from "@warlock.js/ai"`. Skip: composing static system prompts — `@warlock.js/ai/write-system-prompt/SKILL.md`; durable agent memory tiers — `@warlock.js/ai/use-ai-memory/SKILL.md`; defining callable tools — `@warlock.js/ai/define-ai-tool/SKILL.md`.
- [write-system-prompt](@warlock.js/ai/write-system-prompt/SKILL.md): Compose system prompts via ai.systemPrompt() / ai.persona() / ai.instruction() — immutable builders with {{placeholder}} substitution, plus ai.systemPrompt.fromFile(path) to seed from a file read once at construction. Carry identity with .meta({ name, version, description, required }) (a name auto-registers in ai.prompts) and compose with merge(...blocks) / merge(contract) / merge(name, { fromVersion }) (provenance in meta.composedFrom). Triggers: `ai.systemPrompt`, `ai.systemPrompt.fromFile`, `ai.persona`, `ai.instruction`, `SystemPromptBlockContract`, `SystemPromptContract`, `SystemPromptMeta`, `SystemPromptMergeOptions`, `PersonaContract`, `InstructionContract`, `meta`, `merge`, `composedFrom`, `fromVersion`, `placeholders`, `{{placeholder|default}}`, `InvalidRequestError`; 'write a system prompt', 'compose persona + instructions', 'prompt from a file', 'name and version a prompt', 'merge prompts together', 'per-call prompt override', 'mustache placeholder'; typical import `import { ai } from "@warlock.js/ai"`. Skip: the named/versioned prompt registry (register / resolve / tag / diff / export / validate) — `@warlock.js/ai/manage-prompts/SKILL.md`; agent factory wiring — `@warlock.js/ai/run-ai-agent/SKILL.md`; competing libs `langchain` `PromptTemplate`, raw f-strings.