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SDK for the Hermes Memory Lab Agent Service `/api/v1` API.","maintainers":[{"name":"zijunsoft","email":"zijun.soft@gmail.com"}],"readme":"# Agent Service SDK\n\nTypeScript SDK for the Hermes Memory Lab Agent Service `/api/v1` API.\n\nThe SDK is intentionally HTTP-only. It does not import UI code, Next.js route handlers, server adapters, or `AgentCore`.\nUse the server entrypoint for trusted backend code and the browser entrypoint for frontend conversation flows.\n\nFor the full integration guide, see [USAGE.md](./USAGE.md).\n\n## Install\n\nAfter publishing, install the SDK package:\n\n```bash\nnpm install @agent-os-lab/agent-sdk\n```\n\nUse the published entrypoints:\n\n```ts\nimport { AgentServiceServerClient } from \"@agent-os-lab/agent-sdk/server\";\nimport { AgentServiceBrowserClient } from \"@agent-os-lab/agent-sdk/browser\";\nimport type { AgentRunEvent } from \"@agent-os-lab/agent-sdk/types\";\n```\n\nLocal source imports inside this repository use:\n\n```ts\nimport { AgentServiceServerClient } from \"./src/server\";\nimport { AgentServiceBrowserClient } from \"./src/browser\";\n```\n\n## Publish\n\nPublishing is controlled from this SDK package directory. The script bumps the SDK package version, builds the package, runs `npm pack --dry-run`, and then publishes to npm:\n\n```bash\nbun run sdk:publish\n```\n\nThe default release is patch. Use `--minor` or `--major` when needed:\n\n```bash\nbun run sdk:publish -- --minor\n```\n\nUse `--dry-run` to validate the next version and package contents without publishing. The script restores the previous version after a dry run.\n\nIf npm requires two-factor authentication, pass the one-time password with `--otp`:\n\n```bash\nbun run sdk:publish -- --otp 123456\n```\n\n## Runtime\n\n- Node.js 20+ or a modern browser runtime with `fetch`, `Headers`, `Response`, and `ReadableStream`.\n- Runtime dependency: `@ag-ui/client` for AG-UI chat adapters.\n- API keys must never be logged or sent to browsers.\n\n## Local Demo\n\nRun the SDK demo page from this package directory:\n\n```bash\nbun run demo\n```\n\nOpen `http://127.0.0.1:4177`. The demo is a localhost-only Bun server that uses `AgentServiceServerClient` behind a local BFF-style endpoint to test tenant reads, Agents, tool providers, tool drafts, tool connectivity, tools, and tool invocations. The page stores the Agent Service URL, service API key, tenant ID, and subtenant ID in browser `localStorage` for local convenience; it does not persist provider bearer tokens, import the browser client with a service key, or call Agent Service directly from browser code.\n\n## Server Authentication\n\n```ts\nconst client = new AgentServiceServerClient({\n  baseUrl: \"https://agent-service.example.com\",\n  apiKey: process.env.AGENT_SERVICE_API_KEY!,\n  requestId: () => crypto.randomUUID(),\n});\n\nconst { tenant } = await client.getCurrentTenant();\n```\n\nIn production, tenant identity comes from the persisted API key row. `tenantId` is optional in the SDK and should only be supplied for development tenant switching or trusted internal tools:\n\n```ts\nconst localClient = new AgentServiceServerClient({\n  baseUrl: \"http://localhost:3000\",\n  apiKey: \"dev-service-key\",\n  tenantId: \"tenant-demo\",\n});\n```\n\n## Office Game Config From A Tenant BFF\n\nUse the server client to read and save the Office configuration for an authorized subtenant. Agent SDK owns the AgentOS HTTP operation; Game SDK owns the concrete configuration type.\n\n```ts\nimport { AgentServiceServerClient } from \"@agent-os-lab/agent-sdk/server\";\nimport type { AgentGameOfficeConfig } from \"@agent-os-lab/agent-game-sdk/office\";\n\nconst officeClient = new AgentServiceServerClient({\n  baseUrl: process.env.AGENTOS_BASE_URL!,\n  apiKey: process.env.AGENTOS_API_KEY!,\n  subtenantId: authorizedOrgId,\n  requestId: () => crypto.randomUUID(),\n});\n\nconst result = await officeClient.getOfficeGameConfig<AgentGameOfficeConfig>();\nif (result.source !== \"none\") {\n  await officeClient.saveOfficeGameConfig<AgentGameOfficeConfig>(result.config);\n}\n```\n\nThe application must authenticate the browser user and authorize `authorizedOrgId` before using it as the trusted subtenant scope. Browser code calls the application's same-origin BFF; it never receives the AgentOS API key. See [USAGE.md](./USAGE.md) for the response contract and endpoint details.\n\nWhen neither a scoped configuration nor a stored platform default exists, AgentOS returns HTTP 200 with `source: \"none\"` and `config: null`. Handle that branch before reading `config`.\n\n## Browser Authentication\n\nBrowser code must not receive `AGENT_SERVICE_API_KEY`. Use a same-origin business-project BFF/proxy or a short-lived scoped token minted by the business backend:\n\n```ts\nconst client = new AgentServiceBrowserClient({\n  baseUrl: \"/api/agent-service\",\n});\n```\n\n```ts\nconst client = new AgentServiceBrowserClient({\n  baseUrl: \"https://agent-service.example.com\",\n  accessToken: async () => getScopedAgentToken(),\n});\n```\n\n`accessToken` is a business-application user token for the BFF/proxy, not an Agent Service API key. Do not pass tenant API keys, platform admin tokens, or any long-lived service credential to the browser client.\n\nCaller-provided `authorization` and `x-hermes-tenant-id` headers are stripped by the browser client. Only `accessToken` may set a browser bearer token, and only when the business backend expects that browser token.\n\n## AG-UI Chat\n\nUse `createAgUiChat` when building a production chat surface with AG-UI compatible clients such as assistant-ui. It wraps the public AG-UI chat contract for session list/create/read/delete, active-run recovery, and AG-UI agent creation. `threadId` is the AgentOS session ID.\n\nWhen the chat belongs to a tenant customer, team, or account, create the SDK client with the same `subtenantId` used when the session was created. AG-UI session reads are scoped by tenant plus subtenant; omitting `subtenantId` reads the tenant root scope and will not find subtenant sessions.\n\n```ts\nconst chat = browserClient.createAgUiChat({\n  agentId: \"support-agent\",\n  profileId: \"business-user-123\",\n  getAttachmentIds: () => pendingAttachmentIds,\n  getCallableAgentIds: () => currentUserCallableAgentIds,\n});\n\nconst { session } = await chat.createSession();\nconst history = await chat.getSession(session.sessionId);\nconst active = await chat.getActiveRun(session.sessionId);\nconst agent = chat.createAgent({\n  threadId: session.sessionId,\n});\n```\n\nUse `active.run?.runId` as `resumeRunId` in the AG-UI runtime custom run config when reconnecting to an existing run.\n\nFor first-screen bootstrap, prefer summary calls before loading transcript detail:\n\n```ts\nconst latest = await chat.getLatestSessionSummary();\nconst history = latest ? await chat.getSession(latest.sessionId) : null;\n```\n\n`chat.listSessions({ limit: 1 })` and `chat.getLatestSessionSummary()` return compact summaries without messages. `chat.getSession(sessionId)` returns full detail with user-visible transcript messages; internal context compaction summaries are kept for model continuity but are not returned as normal chat messages. Session summaries and full session responses include compression metadata when available: `compactionCount` is the materialized number of completed compression continuations before that session, `contextWindowUsage` is the latest measured context-window usage, and `contextWindowUsage.compressionWindowProgress` contains the computed compression trigger progress (`usedTokens`, `denominatorTokens`, `usedPercent`, and remaining values). `lastCompactionTrace` is present on full session detail when a recent compression trace exists.\n\nPersisted history messages include `messageReference`:\n\n```ts\nconst { session } = await chat.getSession(sessionId);\nconst selectedMessageIds = session.messages\n  .map((message) => message.messageReference?.persistedMessageId)\n  .filter((messageId): messageId is string => Boolean(messageId));\n```\n\nUse `getSessionMessagesByIds` when you already have persisted message ids and only need those messages. This avoids loading the full session transcript and filtering in application code.\n\n```ts\nconst selected = await chat.getSessionMessagesByIds(sessionId, selectedMessageIds);\n```\n\nDuring streaming, AgentOS may emit a `CUSTOM` AG-UI event named `agentos.message.persisted`. Its value maps the current visible runtime message id to the durable persisted message id:\n\n```ts\n{\n  type: \"message.persisted\",\n  runtimeMessageId: \"client-message-id\",\n  persistedMessageId: \"agentos-message-id\"\n}\n```\n\nUse this event as the persistence acknowledgment before treating a streamed message as safe to reference or reload by id.\nAgentOS emits this acknowledgment for persisted visible user and assistant messages. For assistant replies, `runtimeMessageId` matches the AG-UI message id currently visible to the client; `persistedMessageId` is the AgentOS id to store for durable references.\n\nUse the lower-level `createAgUiAgent` when you already own session/history management and only need the AG-UI transport.\n\n```ts\nconst agent = browserClient.createAgUiAgent({\n  agentId: \"support-agent\",\n  threadId: session.sessionId,\n  profileId: \"business-user-123\",\n  getAttachmentIds: () => pendingAttachmentIds,\n});\n\nawait agent.runAgent({\n  modelContext: { userName: \"唐子君\" },\n  toolContext: { businessUserId: \"user-123\" },\n});\n```\n\nUse `modelContext` for hidden model-visible user context. Use `toolContext` only for opaque data that AgentOS tools need.\nBrowser AG-UI agents automatically forward the browser's IANA timezone through\n`forwardedProps.agentos.toolRuntimeContext.timezone`, using\n`Intl.DateTimeFormat().resolvedOptions().timeZone`. Pass\n`toolRuntimeContext.timezone` explicitly to override it for one run.\n\nTrusted backend or BFF code can create the same AG-UI agent from the server client. The server client signs requests with the service API key and tenant scope configured on the client.\n\n```ts\nconst agent = serverClient.createAgUiAgent({\n  agentId: \"support-agent\",\n  threadId: session.sessionId,\n  profileId: \"business-user-123\",\n});\n```\n\nTo recover a running stream after refresh without the facade, call `getAgUiActiveRun(agentId, sessionId, profileId)` and pass the returned run ID through the AG-UI runtime's custom run config as `resumeRunId`.\n\n## Create Profile, Agent, And Stream\n\n```ts\nconst client = new AgentServiceServerClient({\n  baseUrl: \"https://agent-service.example.com\",\n  apiKey: process.env.AGENT_SERVICE_API_KEY!,\n  subtenantId: \"company-a\",\n});\n\nawait client.createProfile({\n  profileId: \"business-user-123\",\n  displayName: \"Business User 123\",\n  metadata: { source: \"billing-app\" },\n});\n\nawait client.createAgent({\n  agentId: \"support-agent\",\n  displayName: \"Support Agent\",\n  systemPrompt: \"You are a support assistant.\",\n  model: \"openai/gpt-5.2\",\n  builtinMemoryEnabled: false,\n  memoryProvider: \"none\",\n  memoryScopeMode: \"both\",\n  compressionEnabled: false,\n  memoryReviewEnabled: false,\n});\n\nconst { bot } = await client.createBot({\n  displayName: \"WeChat Support Bot\",\n  agentId: \"support-agent\",\n});\n\nconst { channelAccount } = await client.createBotChannelAccount(bot.botId, {\n  channelType: \"wechat\",\n  displayName: \"Primary WeChat\",\n});\n\nawait client.refreshBotChannelQrCode(bot.botId, channelAccount.channelAccountId);\n\nconst { session } = await client.createSession(\"support-agent\", {\n  profileId: \"business-user-123\",\n});\n\nfor await (const event of client.streamMessage(\"support-agent\", session.sessionId, {\n  profileId: \"business-user-123\",\n  message: \"Help me understand my invoice.\",\n})) {\n  if (event.type === \"message.delta\") {\n    process.stdout.write(event.delta);\n  }\n  if (event.type === \"tool.started\") {\n    console.log(\"tool started\", event.name);\n  }\n  if (event.type === \"tool.progress\" && event.progress.kind === \"call_agent.child_message_delta\") {\n    process.stdout.write(event.progress.delta);\n  }\n}\n```\n\nAgent routing tools such as `route_agents` and `call_agent` are enabled by the trusted AgentOS runtime host, not by passing functions through SDK request bodies. The SDK sends ordinary HTTP/AG-UI requests; the service runtime injects its configured `CallableAgentResolver` when the run reaches `AgentCore`.\nFor per-user routing, pass the current user's allowed Agent ids with `callableAgentIds` or configure `getCallableAgentIds` on `createAgUiChat`; AgentOS validates tenant scope and `a2aCallable` before exposing `route_agents` / `call_agent`.\n\n`builtinMemoryEnabled` defaults to `true` when omitted. Set it to `false` to fully disable AgentOS built-in memory for the Agent: memory prompts, memory tools, provider reads/writes, review, and flush are skipped. Existing stored memory is not deleted. Session history, `session_search`, wiki, runtime tools, schedules, A2A, and compression still work. When disabled, AgentOS normalizes `memoryProvider` to `\"none\"` and `memoryReviewEnabled` to `false`.\n\n## Subtenant Usage And Export\n\nSet `subtenantId` on `AgentServiceServerClient` when a tenant application needs to isolate resources and billing for one of its own customers, teams, or accounts. Requests made by that client create and read resources inside the subtenant scope, and run/LLM usage is attributed to that same subtenant.\n\n```ts\nconst customerClient = new AgentServiceServerClient({\n  baseUrl: \"https://agent-service.example.com\",\n  apiKey: process.env.AGENT_SERVICE_API_KEY!,\n  subtenantId: \"company-a\",\n});\n```\n\nPull billing events from a trusted backend with `listBillingEvents`. The cursor is `afterSequence`; poll until `hasMore` is false, then store `nextSequence` for the next polling cycle.\n\n```ts\nlet afterSequence = loadLastBillingSequence();\n\nwhile (true) {\n  const page = await client.listBillingEvents({\n    afterSequence,\n    limit: 1000,\n  });\n\n  await saveBillingEvents(page.events);\n  afterSequence = page.nextSequence;\n\n  if (!page.hasMore) {\n    await saveLastBillingSequence(afterSequence);\n    break;\n  }\n}\n```\n\nUse `getUsageSummary` for tenant or subtenant aggregate run usage without pulling billing events or listing Agents first. Add `granularity: \"day\"` when you also need sparse UTC daily buckets for the selected window:\n\n```ts\nconst { usage, series } = await customerClient.getUsageSummary({\n  from: \"2026-05-01T00:00:00.000Z\",\n  to: \"2026-05-31T23:59:59.999Z\",\n  granularity: \"day\",\n});\n\nconsole.log(usage.runs, usage.completedRuns, usage.estimatedCost);\nconsole.log(series?.[0]?.date, series?.[0]?.runs);\n```\n\nUse `getUsage({ agentId })` for a single Agent. Use `getUsageByAgents` when a page needs per-Agent totals for multiple Agents:\n\n```ts\nconst { usageByAgentId } = await customerClient.getUsageByAgents({\n  agentIds: [\"support-agent\", \"sales-agent\"],\n  from: \"2026-05-01T00:00:00.000Z\",\n  to: \"2026-05-31T23:59:59.999Z\",\n});\n```\n\nFor Agent card pages that also need resource badges, use `getAgentResourceCountsByAgents` instead of listing each Agent's tools, skills, schedules, and Wiki pages:\n\n```ts\nconst { countsByAgentId, missingAgentIds } = await customerClient.getAgentResourceCountsByAgents({\n  agentIds: [\"support-agent\", \"sales-agent\"],\n});\n\nconsole.log(countsByAgentId[\"support-agent\"]?.skillCount);\nconsole.log(countsByAgentId[\"support-agent\"]?.defaultToolPermissionCount);\nconsole.log(countsByAgentId[\"support-agent\"]?.activeScheduleCount);\nconsole.log(countsByAgentId[\"support-agent\"]?.knowledgePageCount);\nconsole.log(missingAgentIds);\n```\n\nUse `getLlmUsage` when you need model cost totals and recent generation records:\n\n```ts\nconst { usage } = await customerClient.getLlmUsage({\n  from: \"2026-05-01T00:00:00.000Z\",\n  to: \"2026-05-31T23:59:59.999Z\",\n  status: \"billed\",\n  limit: 100,\n});\n\nconsole.log(usage.totalBilledCost, usage.currency);\nconsole.log(usage.recentGenerations);\n```\n\n## Create A Bot-Owned Agent And Wiki\n\nFor tenant product setup flows, use `createBotBundle` to create a Bot with its own Agent, optional Wiki, and optional channel account in one call. The SDK creates the Wiki first, passes the generated `wikiId` into Agent creation, creates the Bot bound to that Agent, then creates the channel account bound to the Bot.\n\n```ts\nconst { bot, agent, wiki, channelAccount } = await client.createBotBundle({\n  wiki: {\n    displayName: \"Support Knowledge\",\n    description: \"Knowledge used by the support Bot.\",\n  },\n  agent: {\n    displayName: \"Support Agent\",\n    systemPrompt: \"You are a support assistant.\",\n    model: \"openai/gpt-5.2\",\n    builtinMemoryEnabled: false,\n    memoryProvider: \"none\",\n    memoryScopeMode: \"both\",\n    compressionEnabled: false,\n    memoryReviewEnabled: false,\n  },\n  bot: {\n    displayName: \"WeChat Support Bot\",\n    context: { channel: \"wechat\" },\n  },\n  channelAccount: {\n    channelType: \"wechat\",\n    displayName: \"Primary WeChat\",\n  },\n});\n```\n\nDelete the same owned bundle with:\n\n```ts\nawait client.deleteBotBundle(bot.botId);\n```\n\n`deleteBotBundle` atomically deletes the Bot, Agent, Agent bindings, schedules, and exclusively owned Wiki. Repeating the same request is idempotent. Use it only when the Agent is owned by that Bot; shared Agents are rejected.\n\n## Scheduled Agent Tasks\n\nUse schedules from a trusted backend to run an Agent on a one-time, interval, or cron schedule. Scheduled runs use a fresh execution session by default.\n\n```ts\nconst { schedule } = await client.createSchedule(\"support-agent\", {\n  profileId: \"business-user-123\",\n  name: \"Daily support summary\",\n  prompt: \"Summarize yesterday's urgent support issues.\",\n  schedule: \"0 9 * * *\",\n  timezone: \"Asia/Shanghai\",\n  sessionId: \"session-a\",\n});\n\nawait client.pauseSchedule(\"support-agent\", schedule.id);\nawait client.resumeSchedule(\"support-agent\", schedule.id);\nawait client.runScheduleNow(\"support-agent\", schedule.id);\n\nconst { fires } = await client.listScheduleFires(\"support-agent\", schedule.id);\nconst { deliveries } = await client.listScheduleDeliveries(\"support-agent\", schedule.id);\n```\n\n## Skills\n\nSkills are human-authored `SKILL.md` procedures plus optional linked files under `references/`, `templates/`, `scripts/`, or `assets/`. The SDK manages Skills and Agent bindings; runtime execution reads Skills through AgentOS.\n\n```ts\nconst { draft, validation } = await client.createSkillDraft({\n  intent: \"Create a TypeScript backend code review skill.\",\n  category: \"engineering\",\n  tags: [\"review\"],\n});\n\nif (!validation.ok) {\n  throw new Error(validation.errors.join(\"\\n\"));\n}\n\nconst { skill } = await client.createSkill({\n  displayName: draft.displayName,\n  markdown: draft.markdown,\n  files: draft.files,\n  agentIds: [\"agent-a\"],\n});\n```\n\nDraft generation does not save anything. You can also create a Skill directly from a reviewed `SKILL.md`:\n\n```ts\nconst { skill } = await client.createSkill({\n  displayName: \"Code Review\",\n  markdown: `---\nname: code-review\ndescription: Review code changes.\nversion: 1.0.0\nmetadata:\n  agentos:\n    category: engineering\n    tags: [review]\n---\n\n# Code Review\n`,\n  files: [{\n    path: \"references/checklist.md\",\n    contentType: \"text/markdown\",\n    contentText: \"# Checklist\",\n  }],\n});\n\nawait client.setSkillAgentBindings(skill.skill.skillId, {\n  agentIds: [\"support-agent\"],\n});\n\nconst { skills: agentSkills } = await client.listAgentSkills(\"support-agent\");\nconst { wiki } = await client.getAgentWiki(\"support-agent\");\n```\n\n## Agent Groups And A2A\n\nAgent Groups are server-only control-plane APIs. Put Agents in the same group, then mark target Agents callable.\n\n```ts\nawait client.createAgent({\n  agentId: \"crm-analyst\",\n  displayName: \"CRM Analyst\",\n  systemPrompt: \"Analyze CRM records.\",\n  model: \"openai/gpt-5.2\",\n  builtinMemoryEnabled: false,\n  memoryProvider: \"none\",\n  memoryScopeMode: \"both\",\n  compressionEnabled: false,\n  memoryReviewEnabled: false,\n  a2aCallable: true,\n});\n\nawait client.createAgentGroup({\n  groupId: \"sales\",\n  displayName: \"Sales\",\n});\n\nawait client.replaceAgentGroupAgents(\"sales\", {\n  agentIds: [\"support-agent\", \"crm-analyst\"],\n});\n\nawait client.appendAgentGroupAgents(\"sales\", {\n  agentIds: [\"quote-agent\"],\n});\n\nawait client.removeAgentGroupAgents(\"sales\", {\n  agentIds: [\"quote-agent\"],\n});\n\nconst { card } = await client.getA2aAgentCard(\"crm-analyst\");\nconst result = await client.sendA2aMessage(\"crm-analyst\", {\n  callerAgentId: \"support-agent\",\n  profileId: \"business-user-123\",\n  message: \"Summarize this account.\",\n});\n```\n\nAn Agent can call another Agent only when both share at least one Agent Group and the target Agent has `a2aCallable: true`.\n\n## WeChat Bot Binding\n\nBot management is a server-only API. Create the Agent first, then bind a WeChat channel to a Bot:\n\n```ts\nimport {\n  AgentServiceServerClient,\n  SERVICE_BOT_LOGIN_STATUS,\n} from \"@agent-os-lab/agent-sdk/server\";\n\nconst client = new AgentServiceServerClient({\n  baseUrl: \"https://agent-service.example.com\",\n  apiKey: process.env.AGENT_SERVICE_API_KEY!,\n});\n\nconst { bot, channelAccount } = await client.createWechatBotBinding({\n  displayName: \"WeChat Support Bot\",\n  agentId: \"support-agent\",\n  channelDisplayName: \"Primary WeChat\",\n});\n\nawait client.refreshBotChannelQrCode(bot.botId, channelAccount.channelAccountId);\n\nconst { qrCodeText } = await client.waitForBotChannelQrCode(bot.botId, channelAccount.channelAccountId, {\n  timeoutMs: 30000,\n  intervalMs: 1000,\n});\n\nconsole.log(\"Open this WeChat login QR URL:\", qrCodeText);\n\nconst { channelAccounts } = await client.listBotChannelAccounts(bot.botId);\nconst binding = channelAccounts.find((account) => account.channelAccountId === channelAccount.channelAccountId);\n\nif (binding?.runtimeState?.loginStatus === SERVICE_BOT_LOGIN_STATUS.loggedIn) {\n  console.log(\"WeChat binding is logged in.\");\n}\n```\n\n`createWechatBotBinding` does not accept a `botId`; Agent Service generates it. The QR code is returned as a URL string in `qrCodeText`, so render it as a link or open it in a new page.\n\n## Tenant HTTP Tools\n\nTool provider registration, tool definition, Agent binding, and invocation reads are server-only APIs:\n\n```ts\nconst { provider } = await client.createToolProvider({\n  name: \"crm\",\n  displayName: \"Customer CRM\",\n  baseUrl: \"https://crm.example.com/agentos\",\n  headers: { \"x-provider-region\": \"us\" },\n  auth: { type: \"bearer\", token: process.env.CRM_AGENTOS_TOKEN! },\n});\n\n// Omit auth for providers that do not need bearer authentication.\n\nawait client.upsertTool(provider.providerId, \"profile_completion.update\", {\n  displayName: \"Update profile completion\",\n  description: \"Update profile completion percentage.\",\n  inputSchema: {\n    type: \"object\",\n    required: [\"percent\"],\n    properties: {\n      percent: { type: \"number\", minimum: 0, maximum: 100 },\n    },\n    additionalProperties: false,\n  },\n  executor: {\n    type: \"http\",\n    method: \"PATCH\",\n    path: \"/tools/profile-completion/update\",\n    timeoutMs: 5000,\n    headers: { \"x-crm-feature\": \"profile-write\" },\n  },\n  contextPolicy: { includeMessageContext: true, requireMessageContext: true },\n  resultPolicy: \"hidden\",\n});\n\nawait client.setAgentTools(\"support-agent\", {\n  tools: [\"crm.profile_completion.update\"],\n});\n```\n\n`name` and `toolName` are stable identifiers used for bindings and model tool names. `displayName` is optional UI text returned by read APIs; omit it or set it to `null` to display the stable identifier instead.\n\nUse `listToolProviderTools` for tool-picker or bootstrap screens that need providers and their tools in one lightweight request:\n\n```ts\nconst { providers } = await client.listToolProviderTools({\n  status: \"enabled\",\n});\n```\n\nThis returns provider and tool summaries only. It does not include provider credentials, provider headers, tool input schemas, or executor configuration.\n\nGenerate draft tool definitions from an API document when you want a review step before registration:\n\n```ts\nconst { drafts } = await client.createToolDrafts(provider.providerId, {\n  apiDocument: openApiOrMarkdownText,\n  endpointHints: [\"PATCH /tools/profile-completion/update\"],\n  maxDrafts: 5,\n});\n\nfor (const draft of drafts) {\n  await client.upsertTool(provider.providerId, draft.toolName, {\n    displayName: draft.displayName,\n    description: draft.description,\n    inputSchema: draft.inputSchema,\n    executor: draft.executor,\n    contextPolicy: draft.contextPolicy,\n    resultPolicy: draft.resultPolicy,\n    status: draft.status,\n  });\n}\n```\n\nDraft generation is not persisted. Review the returned drafts before saving them; `upsertTool` validates the schema again. `apiDocument` is limited to 200,000 characters, `endpointHints` to 50 items of 2,000 characters each, and `maxDrafts` to 1-20.\n\nTest a registered tool's connectivity from trusted backend code:\n\n```ts\nconst { test } = await client.testTool(provider.providerId, \"profile_completion.update\", {\n  input: { percent: 80 },\n  context: { businessUserId: \"user-123\" },\n});\n\nconsole.log(test.ok, test.status, test.errorCode);\n```\n\nThis sends a real POST to the provider endpoint with `x-agentos-test-call: true`; provider handlers should avoid mutating production data for test calls.\n\nSend opaque business context per message when a tool needs to identify the business-side user:\n\n```ts\nawait client.sendMessage(\"support-agent\", session.sessionId, {\n  profileId: \"business-user-123\",\n  message: \"Update this user's profile completion.\",\n  toolContext: { businessUserId: \"user-123\" },\n});\n```\n\nAgent Service does not interpret the tool context object. It stores it with the user message and forwards it to tools according to each tool's `contextPolicy`.\n\nProduction tool setup also requires `AGENTOS_USER_DATA_ENCRYPTION_KEY` in Agent Service so provider credentials can be encrypted at rest. The full tools guide covers schema support, HTTP request shape, raw HTTP responses, error codes, token rotation, and business-side handler examples in [USAGE.md](./USAGE.md#tenant-http-tools).\n\n## MCP Servers\n\nMCP management is server-only. Register remote Streamable HTTP MCP servers from trusted backend code, then bind them to Agents:\n\n```ts\nconst { server } = await client.createMcpServer({\n  name: \"crm\",\n  displayName: \"CRM MCP\",\n\t  transport: {\n\t    type: \"streamable-http\",\n\t    url: \"https://crm.example.com/mcp\",\n\t  },\n\t  credential: {\n\t    type: \"agentos-runtime-jwt-jwks\",\n\t    audience: \"crm-mcp\",\n\t  },\n\t});\n\nawait client.setAgentMcpServers(\"support-agent\", {\n  servers: [{\n    mcpServerId: server.mcpServerId,\n    enabled: true,\n    toolNameFilter: { include: [\"customer_search\"], exclude: [\"admin_delete\"] },\n  }],\n});\n```\n\nAt runtime, AgentOS calls MCP `tools/list` with a short-lived Bearer token. The token includes AgentOS runtime claims such as tenant, Agent, profile, MCP server, operation, and nested `tool_context` when SDK `toolContext` was supplied. The MCP server filters the returned tools according to its own permission model, so AgentOS only injects the allowed tools for that turn.\n\nTenant MCP servers verify AgentOS runtime JWTs through public metadata:\n\n```ts\nconst discovery = await client.getMcpRuntimeJwtDiscovery();\nconst jwks = await client.getMcpRuntimeJwtJwks();\n```\n\nUse `agentos-runtime-jwt-jwks` for tenant-facing MCP servers. The full guide covers discovery/JWKS claims, binding filters, and invocation diagnostics in [USAGE.md](./USAGE.md#mcp-servers).\n\nFrontend chat surfaces should use the browser client against a BFF/proxy:\n\n```ts\nconst browserClient = new AgentServiceBrowserClient({\n  baseUrl: \"/api/agent-service\",\n});\n\nconst { session } = await browserClient.createSession(\"support-agent\", {\n  profileId: \"business-user-123\",\n});\n\nconst latest = await browserClient.getLatestSessionSummary(\"support-agent\", \"business-user-123\");\n\nfor await (const event of browserClient.streamMessage(\"support-agent\", session.sessionId, {\n  profileId: \"business-user-123\",\n  message: \"Help me understand my invoice.\",\n})) {\n  if (event.type === \"message.delta\") {\n    appendAssistantDelta(event.delta);\n  }\n}\n```\n\n## Attachments\n\nAttachments are uploaded directly from the browser to the Agent Service configured object store. When the upload is confirmed, Agent Service reads the object, calls file2md, and stores the converted Markdown during the confirm request. Send only `converted` attachment IDs with a message or queued run.\n\n```ts\nconst created = await browserClient.createAttachmentUpload(\"support-agent\", session.sessionId, {\n  profileId: \"business-user-123\",\n  filename: file.name,\n  contentType: file.type || \"application/octet-stream\",\n  sizeBytes: file.size,\n});\n\nawait fetch(created.upload.url, {\n  method: created.upload.method,\n  headers: created.upload.headers,\n  body: file,\n});\n\nconst { attachment } = (\n  await browserClient.confirmAttachmentUpload(\"support-agent\", session.sessionId, created.attachment.id, {\n    profileId: \"business-user-123\",\n  })\n);\n\nif (attachment.status !== \"converted\") {\n  throw new Error(attachment.conversionError ?? \"Attachment conversion failed.\");\n}\n\nconst withMarkdown = await browserClient.getSessionAttachment(\n  \"support-agent\",\n  session.sessionId,\n  attachment.id,\n  \"business-user-123\",\n  { includeMarkdown: true, includeDownloadUrl: true },\n);\n\nconsole.log(withMarkdown.attachment.markdown);\nconsole.log(withMarkdown.attachment.downloadUrl);\n\nawait browserClient.sendMessage(\"support-agent\", session.sessionId, {\n  profileId: \"business-user-123\",\n  message: \"Analyze this file.\",\n  attachmentIds: [attachment.id],\n});\n```\n\nAvailable methods:\n\n- `createAttachmentUpload`\n- `confirmAttachmentUpload`\n- `listSessionAttachments`\n- `getSessionAttachment` (`{ includeMarkdown: true }` returns the converted Markdown, `{ includeDownloadUrl: true }` returns a short-lived original-file download URL)\n- `retrySessionAttachment`\n\nConverted Markdown is complete. By default attachment read APIs return only metadata. Agent Service rejects oversized attachment prompts instead of truncating them.\n\n## Wiki Overview And Lists\n\nUse `getWikiOverview` for Agent detail pages or Wiki cards that need the Wiki title, small source/page/job panels, and status counters in one bounded request:\n\n```ts\nconst overview = await client.getWikiOverview(\"wiki-a\", {\n  sourceLimit: 10,\n  pageLimit: 10,\n  jobLimit: 5,\n});\n\nconsole.log(overview.counts?.pageCount);\nconsole.log(overview.sources);\n```\n\nOverview and list responses return summaries. Source and page summaries omit `markdown`; job summaries omit `trace`. Read a single source, page, or job detail only when the UI needs the detail payload.\n\nSDK Wiki list methods use cursor pagination by default:\n\n```ts\nconst wikiList = await client.listWikis({ page: 1, pageSize: 50 });\n\nconsole.log(wikiList.totalCount);\n\nlet page = await client.listWikiSources(\"wiki-a\", { limit: 20, status: \"ready\" });\n\nwhile (page.nextCursor) {\n  page = await client.listWikiSources(\"wiki-a\", {\n    cursor: page.nextCursor,\n    limit: 20,\n    status: \"ready\",\n  });\n}\n```\n\n`listWikiSources` and `listWikiPages` exclude archived rows unless a `status` filter is provided. `listWikiJobs` returns all job statuses unless filtered.\n\nUse `rebuildWiki` to queue a full regeneration from the Wiki's current non-archived sources:\n\n```ts\nconst { job } = await client.rebuildWiki(\"wiki-a\");\n\nconsole.log(job.jobType); // \"rebuild\"\n```\n\n## Wiki File Uploads\n\nUse `uploadConsoleFile` when you need the converted Markdown. Use `uploadAndCreateWikiSource` when you want to upload a file, wait for conversion, and attach the converted file to a Wiki as a file-backed source in one SDK call. The Wiki source keeps the originating `fileId`; the SDK no longer sends the converted Markdown back in the create-source request.\n\n```ts\nimport { uploadAndCreateWikiSource, uploadConsoleFile } from \"@agent-os-lab/agent-sdk\";\n\nconst converted = await uploadConsoleFile({\n  client,\n  file,\n});\n\nconsole.log(converted.markdown);\n\nconst { source } = await uploadAndCreateWikiSource({\n  client,\n  wikiId: \"wiki-a\",\n  file,\n});\n\nconsole.log(source.fileId);\n\nconst existingFileSource = await client.createWikiSourceFromFile(\"wiki-a\", {\n  fileId: converted.id,\n});\n\nconsole.log(existingFileSource.source.id);\n\nconst removal = await client.deleteWikiSource(\"wiki-a\", source.id);\n\nconsole.log(removal.source.status); // \"archived\"\nconsole.log(removal.job.jobType); // \"source_removed\"\n```\n\n`deleteWikiSource` archives a `ready` or `failed` Wiki source and creates a `source_removed` Wiki job so generated pages can be updated without that source. Sources that are still `uploaded` or `converting` return a conflict response.\n\nLower-level file methods are also available:\n\n- `createConsoleFileUpload`\n- `confirmConsoleFileUpload`\n- `getConsoleFile`\n- `retryConsoleFile`\n- `createWikiSourceFromFile`\n\n## Async Runs\n\nAsync runs require a runtime worker process in the Agent Service environment.\n\n```ts\nconst created = await client.createRun(\"support-agent\", {\n  profileId: \"business-user-123\",\n  sessionId: session.sessionId,\n  message: \"Summarize my open invoices.\",\n  toolContext: { businessUserId: \"user-123\" },\n  toolRuntimeContext: { timezone: \"Asia/Shanghai\" },\n});\n\nlet run = created.run;\nwhile (run.status === \"queued\" || run.status === \"running\") {\n  await new Promise((resolve) => setTimeout(resolve, 1000));\n  run = (await client.getRun(\"support-agent\", run.runId)).run;\n}\n\nconst replay = await client.listRunEvents(\"support-agent\", run.runId);\n```\n\nUse `toolRuntimeContext.timezone` for user-semantic date phrases such as\n`today`, `tomorrow`, and `yesterday` in async runs. Browser AG-UI runs set this\nautomatically; backend-created runs should pass the user's IANA timezone when it\nis known.\n\n## Memory\n\nMemory APIs are server-only. Use `readMemory` for one profile's full memory state, and `listMemories` for lightweight paginated inspection across profiles for one Agent:\n\n```ts\nconst { memories, nextCursor } = await client.listMemories(\"support-agent\", {\n  limit: 50,\n  scope: \"shared-profile\",\n});\n\nfor (const entry of memories) {\n  console.log(entry.profileId, entry.scope, entry.target, entry.content);\n}\n```\n\nUse `clearAgentMemory` to clear active private memory for an Agent. Pass `profileId`, `scope`, or `target` to narrow the operation. Clearing `shared-profile` memory requires `profileId` because that memory is shared across Agents for the same profile.\n\n```ts\nawait client.clearAgentMemory(\"support-agent\", {\n  profileId: \"business-user-123\",\n  scope: \"agent-private\",\n});\n```\n\n`listMemories` returns memory entry summaries only. It does not fetch session transcripts or session detail.\nWhen using `query`, also pass `profileId`; cross-profile content search is intentionally not part of this lightweight list endpoint.\n\n## Webhooks\n\n```ts\nconst { webhook, secret } = await client.createWebhook({\n  url: \"https://billing.example.com/hermes-webhooks\",\n  eventTypes: [\"run.completed\", \"run.failed\", \"run.cancelled\"],\n});\n```\n\nThe raw webhook `secret` is returned once. Store it securely and verify `x-hermes-webhook-signature` in the receiver. Do not log the secret.\n\n## Error Handling\n\n```ts\nimport { AgentServiceError } from \"@agent-os-lab/agent-sdk/server\";\n\ntry {\n  await client.getAgent(\"missing-agent\");\n} catch (error) {\n  if (error instanceof AgentServiceError) {\n    console.error({\n      status: error.status,\n      code: error.code,\n      requestId: error.requestId,\n      details: error.details,\n    });\n  }\n  throw error;\n}\n```\n\n## Request Options\n\nEvery SDK method accepts optional request options as the final parameter:\n\n```ts\nconst controller = new AbortController();\n\nawait client.sendMessage(\"support-agent\", \"session-id\", {\n  profileId: \"business-user-123\",\n  message: \"Hello\",\n}, {\n  requestId: \"business-request-123\",\n  signal: controller.signal,\n  headers: {\n    \"x-business-workflow-id\": \"workflow-123\",\n  },\n});\n```\n\nThe browser client accepts the same `requestId`, `signal`, and safe custom headers, but strips caller-provided `authorization` and `x-hermes-tenant-id`.\n\n## Delete Semantics\n\nDelete operations archive or deactivate control-plane resources. `deleteAgent` and `deleteProfile` remove resources from normal SDK reads and writes, but historical sessions, runs, messages, memory audit data, and cost ledger records remain available to the platform for audit and retention. `deleteWikiSource` archives the source and queues a `source_removed` Wiki job. API key deletion revokes the key instead of removing its audit record.\n\n## Coverage\n\nThe server SDK covers tenant-scoped agent registry, profile registry, sessions, streaming, async runs, memory, session search, lineage, billing event export, tenant HTTP tools, and webhooks.\n\nThe browser SDK covers the current-user conversation surface: sessions, sync messages, streaming messages, async runs, run polling, cancellation, and run event replay.\n\n## 0.2.0 Breaking Change\n\n`OfficeGameConfigResponse` now includes `{ config: null, updatedAt: null, source: \"none\" }`. Check `source` before reading `config`; AgentOS no longer substitutes a code-built Office default when persistence is empty.\n","readmeFilename":"README.md"}