> ## Documentation Index > Fetch the complete documentation index at: https://cadenya.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Get objective context diagnostics > Returns the context-usage breakdown measured for the objective's most recent iteration: character lengths per context component (system prompt, memory appendices, tool definitions, messages by role) alongside the iteration's input token counts. ## OpenAPI ````yaml /api-spec.yml get /v1/workspaces/{workspaceId}/objectives/{objectiveId}/diagnostics openapi: 3.1.0 info: title: Cadenya API description: API for the Cadenya Agent Runtime platform. version: '1.0' servers: - url: https://api.cadenya.com description: Production server security: - bearerAuth: [] tags: - name: AIProviderKeyService - name: APIKeyService description: |- Issue, rotate, disable, and revoke a workspace's API keys. Every key belongs to exactly one workspace; the system-managed global account key is managed via GlobalAPIKeyService instead. - name: AccountService description: >- Manage the authenticated account. Accounts are the top-level organizational unit and contain one or more workspaces. - name: AgentScheduleService description: >- Manage recurring schedules attached to agents. Schedules trigger objectives on a cadence defined by AgentScheduleSpec.Schedule. - name: AgentService description: >- Manage AI agents within a workspace. Agents define AI behavior and tool access. - name: AgentVariationService description: >- Manage variations of an agent and their tool, sub-agent, and memory layer assignments. - name: GlobalAPIKeyService description: |- Manage the account's system-provisioned global API key. The global key is the only key that spans every workspace; it is created by the system and cannot be deleted, so the surface is retrieve, rotate, and the disable/enable kill switch. - name: MemoryService description: >- Manage memory layers and their entries. Layers are named containers that can be composed into an objective's memory cascade; entries are the keyed values within a layer. System-managed layers (e.g., episodic layers created by the runtime) cannot be mutated through this API. - name: ModelService description: |- Manage LLM models available to a workspace. Models represent provider and family pairs (e.g., "anthropic/claude-sonnet-4.6"). Workspaces are seeded with the supported models and you can enable or disable each one. - name: ObjectiveEventStreamsService - name: ObjectiveService - name: ProfilesService description: |- Operations on profiles, the account-level principals (users, API keys, system) that authenticate against the API. - name: SearchService - name: TenantService description: >- Read and erase tenants and the subjects under them. Tenants and subjects are created by assertion — on objective creation or widget session mint — never directly, so this service has no create or update: it exists to enumerate what assertions have produced, and to destroy it on request. - name: ToolService description: >- Manage tool sets and the tools they contain. Tool sets group related tools, and tools define specific capabilities available to agents. When a tool set is managed, only API key actors can modify its tools; human (profile) actors cannot. - name: UploadService description: |- Issue short-lived presigned URLs for direct client-to-object-storage uploads. Created uploads can be referenced by id when creating or updating resources that accept binary content (e.g., MemoryEntry). - name: WidgetService description: |- Manage embeddable chat widgets. A widget binds an agent to a globally unique hostname with a per-widget origin allowlist; browsers reach it with session tokens minted via WidgetSessionService. - name: WidgetSessionService description: >- Mint and manage widget sessions. Session creation is server-to-server only: the customer's backend authenticates its visitor, asserts tenant/subject context, attaches any per-visitor secrets, and receives a short-lived bearer token the browser uses against the widget host. - name: WorkspaceAdminService description: >- Administer workspaces across the account: create and archive workspaces and manage their membership. These operations are account-scoped and require the admin role (a token whose profile holds the WorkOS admin role); they live under /v1/account/workspaces rather than the workspace-scoped /v1/workspaces tree so an admin can manage any workspace in the account, including ones they are not themselves a member of. - name: WorkspaceSecretService - name: WorkspaceService description: |- Manage workspaces within an account. Workspaces provide organizational grouping and isolation for resources such as agents, tools, and API keys. This is the workspace-scoped, end-user surface. Administrative operations (create / archive workspaces, manage members) live in WorkspaceAdminService under /v1/account/workspaces and require the admin role. paths: /v1/workspaces/{workspaceId}/objectives/{objectiveId}/diagnostics: get: tags: - ObjectiveService - Objectives summary: Get objective context diagnostics description: >- Returns the context-usage breakdown measured for the objective's most recent iteration: character lengths per context component (system prompt, memory appendices, tool definitions, messages by role) alongside the iteration's input token counts. operationId: ObjectiveService_GetObjectiveDiagnostics parameters: - name: workspaceId in: path required: true schema: type: string example: workspace_01HXKD2E5NQM3T9AYWCF133E3Q - name: objectiveId in: path description: >- The ID of the objective. Supports "external_id:" prefix for external IDs. required: true schema: example: obj_01HXKD2E5NQM3T9AYWCFQAZGFV type: string responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/GetObjectiveDiagnosticsResponse' default: description: Default error response content: application/json: schema: $ref: '#/components/schemas/Status' x-codeSamples: - lang: typescript label: TypeScript source: >- import Cadenya from '@cadenya/cadenya'; const client = new Cadenya(); const result = await client.objectives.retrieveDiagnostics('objective_123'); - lang: go label: Go source: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\t\"log\"\n\n\tcadenya \"go.cadenya.com/cadenya-go\"\n)\n\nfunc main() {\n\tclient, err := cadenya.NewClient()\n\tif err != nil {\n\t\tlog.Fatal(err)\n\t}\n\tctx := context.Background()\n\tparams := &cadenya.ObjectiveRetrieveDiagnosticsParams{}\n\tresult, err := client.Objectives().RetrieveDiagnostics(ctx, \"objective_123\", params)\n\tif err != nil {\n\t\tlog.Fatal(err)\n\t}\n\tfmt.Printf(\"%+v\\n\", result)\n}" - lang: python label: Python source: |- from cadenya import Cadenya with Cadenya() as client: result = client.objectives.retrieve_diagnostics("objective_123") print(result) - lang: ruby label: Ruby source: |- require "cadenya" client = Cadenya::Client.new result = client.objectives.retrieve_diagnostics("objective_123") puts result.inspect - lang: shell label: CLI source: cadenya objectives retrieve-diagnostics objective_123 components: schemas: GetObjectiveDiagnosticsResponse: required: - diagnostics type: object properties: diagnostics: readOnly: true allOf: - $ref: '#/components/schemas/ObjectiveDiagnostics' description: Diagnostics from the objective's most recent iteration. Status: type: object properties: code: type: integer description: >- The status code, which should be an enum value of [google.rpc.Code][google.rpc.Code]. format: int32 message: type: string description: >- A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the [google.rpc.Status.details][google.rpc.Status.details] field, or localized by the client. details: type: array items: $ref: '#/components/schemas/GoogleProtobufAny' description: >- A list of messages that carry the error details. There is a common set of message types for APIs to use. description: >- The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). ObjectiveDiagnostics: required: - contextLengths - inputTokens - cachedInputTokens type: object properties: contextLengths: readOnly: true allOf: - $ref: '#/components/schemas/ContextLengths' description: Measured character lengths per context component. inputTokens: readOnly: true type: integer description: >- Input tokens reported by the LLM provider for the iteration's completion. format: int32 cachedInputTokens: readOnly: true type: integer description: |- The portion of input_tokens served from the provider's prompt cache. Lets clients distinguish "big but cached" from "big and paid fresh every iteration". format: int32 description: >- ObjectiveDiagnostics is the context-usage breakdown measured for a single iteration at request-assembly time. It reports how much of the context window each component occupies so tool parameters, memory cascades, and prompts can be tuned against real token usage. GoogleProtobufAny: type: object properties: '@type': type: string description: The type of the serialized message. additionalProperties: true description: >- Contains an arbitrary serialized message along with a @type that describes the type of the serialized message. ContextLengths: required: - systemPrompt - skillsMemory - episodicMemory - availableTools - toolDefinitions - userMessages - assistantMessages - toolResults type: object properties: systemPrompt: readOnly: true type: integer description: >- Character length of the objective's base system prompt (rendered variation template). Not tokens -- see the message comment. format: int32 skillsMemory: readOnly: true type: integer description: >- Character length of the skills memory appendix attached to the system prompt. format: int32 episodicMemory: readOnly: true type: integer description: >- Character length of the episodic memory appendix attached to the system prompt. format: int32 availableTools: readOnly: true type: integer description: >- Character length of the discoverable/available-tools appendix attached to the system prompt. format: int32 toolDefinitions: readOnly: true type: integer description: >- Character length of the serialized tool definitions sent with the completion request (names, descriptions, and JSON-schema parameters). format: int32 userMessages: readOnly: true type: integer description: Character length of the chat history messages with the user role. format: int32 assistantMessages: readOnly: true type: integer description: >- Character length of the chat history messages with the assistant role. format: int32 toolResults: readOnly: true type: integer description: Character length of the tool results present in the chat history. format: int32 description: >- ContextLengths is the measured character length of each distinct component of an iteration's assembled context window. Values are raw character lengths of the component as assembled into the request — token estimates are derived by the client against input_tokens (component share = component length / sum of all lengths). New components are added as new fields — wire-compatible; absent components read as 0. securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: JWT ````