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Discover and install skills, docs, and rules to enhance your AI agent's capabilities.

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imaging-data-commons

synthetic-sciences/openscience

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

Skills

synthetic-sciences/openscience

Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.

Skills

synthetic-sciences/openscience

Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.

Skills

synthetic-sciences/openscience

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

Skills

letta-ai/letta-code

Identify and repair degradation in system prompt, external memory, and skills preventing you from following instructions or remembering information as well as you should.

Skills

Isomorphic tool system: toolDefinition() with Zod schemas, .server() and .client() implementations, passing tools to both chat() on server and useChat/clientTools on client, tool approval flows with needsApproval and bound interrupts (resolveInterrupt), generic middleware interrupts with defineInterrupt(), lazy tool discovery with lazy:true, rendering ToolCallPart and ToolResultPart in UI.

Skills

Type-safe JSON schema responses from LLMs using outputSchema on chat() and useChat(). Supports Zod, ArkType, and Valibot schemas. The adapter handles provider-specific strategies transparently — never configure structured output at the provider level. Pass stream:true alongside outputSchema for incremental JSON deltas + a completed typed object via the `structured-output.complete` event. Each successfully completed structured-output run adds a typed `StructuredOutputPart` to message history. partial/final derive from the most recent structured-output part after the latest user message. convertSchemaToJsonSchema() for manual schema conversion.

Skills

Chat lifecycle middleware hooks: onConfig, onStart, onChunk, onBeforeToolCall, onAfterToolCall, onUsage, onFinish, onAbort, onError. Use for analytics, event firing, tool caching (toolCacheMiddleware), logging, and tracing. Middleware array in chat() config, left-to-right execution order. NOT onEnd/onFinish callbacks on chat() — use middleware.

Skills

Image, audio, video, speech (TTS), and transcription generation using activity-specific adapters: generateImage() with openaiImage/geminiImage/byteplusImage, generateAudio() with geminiAudio/falAudio, generateVideo() with async polling (openaiVideo/geminiVideo/grokVideo/falVideo/byteplusVideo/openRouterVideo, per-model typed durations), generateSpeech() with openaiSpeech/byteplusSpeech, generateTranscription() with openaiTranscription/byteplusTranscription. React hooks: useGenerateImage, useGenerateAudio, useGenerateSpeech, useTranscription, useGenerateVideo. TanStack Start server function integration with toServerSentEventsResponse.

Skills

TanStack/ai

LockStore, InMemoryLockStore, LocksCapability and withLocks for multi-instance coordination in TanStack AI. Ships in @tanstack/ai — NOT in @tanstack/ai-persistence. Separate from AIPersistence state stores — not a stores key, not composable. InMemoryLockStore vs a distributed (e.g. Cloudflare Durable Object) lock, lease recovery, AbortSignal in critical sections. Use when sandbox or other middleware needs cross-worker mutual exclusion — NOT for storing messages/runs (use withPersistence).

Skills

Pluggable, category-toggleable debug logging for TanStack AI activities. Toggle with `debug: true | false | DebugConfig` on chat(), summarize(), generateImage(), generateSpeech(), generateTranscription(), generateVideo(). Categories: request, provider, output, middleware, tools, agentLoop, config, errors. Pipe into pino/winston/etc via `debug: { logger }`. Errors log by default even when `debug` is omitted; silence with `debug: false`.

Skills

Connect useChat to a non-TanStack-AI backend through custom connection adapters. ConnectConnectionAdapter (single async iterable) vs SubscribeConnectionAdapter (separate subscribe/send). Customize fetchServerSentEvents() and fetchHttpStream() with auth headers, custom URLs, and request options. Import from framework package, not @tanstack/ai-client.

Skills

Browser chat persistence on useChat / ChatClient: localStoragePersistence, sessionStoragePersistence, indexedDBPersistence. Client-authoritative (adapter, full transcript) vs server-authoritative (persistence: true, no client cache). Reload restore, pending interrupts, mid-stream rejoin with delivery durability. Use for SPA reload durability — NOT server history alone. Also covers generation hooks (useGenerateImage etc.), which take only the server-driven mode: persistence: true hydrates the last generation for the (REQUIRED) threadId from the server on mount and repaints status/result/error, nothing is cached in the browser. No extra package: the adapters ship in the framework packages.

Skills

Server-side AG-UI streaming protocol implementation: StreamChunk event types (RUN_STARTED, TEXT_MESSAGE_START/CONTENT/END, TOOL_CALL_START/ARGS/END, RUN_FINISHED, RUN_ERROR, STEP_STARTED/STEP_FINISHED, STATE_SNAPSHOT/DELTA, CUSTOM), toServerSentEventsStream() for SSE format, toHttpStream() for NDJSON format. For backends serving AG-UI events without client packages.

Skills

Provider adapter selection and configuration: openaiText, anthropicText, geminiText, ollamaText, grokText, groqText, openRouterText, bedrockText, byteplusText, openaiCompatible. Per-model type safety with modelOptions, reasoning/thinking configuration, runtime adapter switching, extendAdapter() for custom models, createModel(). Generic OpenAI-compatible providers (DeepSeek, Together, Fireworks, etc.) via openaiCompatible({ baseURL, apiKey, models }) from @tanstack/ai-openai/compatible. API key env vars: OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY/GEMINI_API_KEY, XAI_API_KEY, GROQ_API_KEY, OPENROUTER_API_KEY, OLLAMA_HOST, BEDROCK_API_KEY (or AWS_BEARER_TOKEN_BEDROCK). BytePlus needs TWO keys: ARK_API_KEY (ModelArk — chat/video/image) and BYTEPLUS_VOICE_API_KEY (Seed Speech — TTS/transcription); neither is a fallback for the other.

Skills

TanStack/ai

Run harness adapters (Claude Code, Codex, OpenCode) INSIDE isolated sandboxes via defineSandbox + withSandbox + a provider (localProcessSandbox / dockerSandbox). Covers declarative provisioning: createSecrets + secret/bearer, skills (agentSkill/gitSkill/mcpSkill/ fileSkill), plugins, instructions → canonical AGENTS.md + symlinks projected per harness; shallow-clone default with depth opt-out; serial/parallel setup callback over a persistent shell; snapshot-after-setup default with snapshotMaxAge TTL. It also covers portable snapshots after a successful terminal run with withPersistence before withSandbox and memorySandboxSnapshots for local examples. It covers named saves with snapshots.save, selected-checkpoint forks with snapshots.fork, and authorized artifact reads with snapshots.readArtifact. See docs/sandbox/portable-snapshots.md. It covers defineWorkspace (git/setup/scripts/skills/secrets/ instructions/plugins), defineSandboxPolicy (allow/ask/deny), lifecycle/resume, the SandboxHandle (fs/git/process/ports), capability tokens, defineSandbox hooks (onFile/onFileCreate/onFileChange/onFileDelete/onReady/onError/ onDestroy) + fileEvents flag, chat middleware sandbox group (defineChatMiddleware sandbox hooks), the sandbox debug category, watchWorkspace as a low-level building block, the file.changed / sandbox.file / claude-code.session-id events, and the run journal (spawnNdjson journal option, runId uniqueness, follow vs bounded-poll reading, alignToStoredLog replay alignment, chunkFingerprint, createRunScopedIdGen), and takeover of detached runs (withSandbox runs+durability as one opt-in, detach vs cancel via requestRunCancel / RUN_CANCEL_REASON, sandboxRunDriver on the resume path, single-writer fencing of BOTH the event log and the run record, replay-from-zero with JournalReplayDivergedError, the distributed LockStore requirement). Use whenever a harness adapter needs a sandbox or when building sandbox providers.

Skills

Implement the MessageStore, RunStore, InterruptStore, MetadataStore contracts for @tanstack/ai-persistence against any database. defineAIPersistence, composePersistence overrides, critical invariants (full-replace saveThread, insert-if-absent createOrResume and interrupt create), authorize thread access, runPersistenceConformance testkit. Use whenever you need server persistence — the package ships contracts, not a backend for your database.

Skills

Server chat state with withPersistence from @tanstack/ai-persistence. Authoritative transcript, run lifecycle, durable interrupts/approvals, chatParamsFromRequest, reconstructChat, snapshotStreaming. Use when the server owns history, multi-device, or durable tool approvals. NOT client localStorage (see ai-core/client-persistence in @tanstack/ai) and NOT stream reconnect alone.

Skills

Use when an app already runs Prisma and needs TanStack AI chat persistence — writes a chat-persistence.ts into the app against its existing PrismaClient and schema.prisma. Covers the four models, BigInt timestamps, JSON-as-string columns, upsert-with-empty-update idempotency, and model renaming.

Skills

Use when an app already runs Drizzle ORM and needs TanStack AI chat persistence — writes a chat-persistence.ts into the app against its existing db handle, schema file, and drizzle-kit journal. Covers the four tables (SQLite/Postgres/MySQL), the onConflict idempotency rules, JSON columns, and per-request bindings like D1.

Skills

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