> ## Documentation Index > Fetch the complete documentation index at: https://docs.cekura.ai/llms.txt > Use this file to discover all available pages before exploring further. # Update Metric > Partially update a metric. Same field shape as create — see `metrics_create` for details. ## OpenAPI ````yaml patch /test_framework/v1/metrics/{id}/ openapi: 3.1.0 info: title: Cekura API version: v1 description: >- Complete API documentation for the Cekura platform. This API provides endpoints for testing, observing, and evaluating AI voice agents — including managing agents, running evaluators, defining metrics, and analyzing call quality. servers: - url: https://api.cekura.ai security: [] paths: /test_framework/v1/metrics/{id}/: patch: tags: - Metrics summary: Update a metric (partial) description: >- Partially update a metric. Same field shape as create — see `metrics_create` for details. **Note:** `project` and `agent` are read-only once set — you cannot move a metric between projects/agents after creation. To relocate, create a new metric and delete the old one. operationId: metrics-partial-update parameters: - in: path name: id schema: type: integer description: A unique integer value identifying this metric. required: true requestBody: content: application/json: schema: $ref: '#/components/schemas/PatchedSchemaPostMetricEdit' examples: UpdatePrompt+CriticalFlag: value: description: Updated rubric is_critical: true summary: Update prompt + critical flag application/x-www-form-urlencoded: schema: $ref: '#/components/schemas/PatchedSchemaPostMetricEdit' multipart/form-data: schema: $ref: '#/components/schemas/PatchedSchemaPostMetricEdit' responses: '200': content: application/json: schema: $ref: '#/components/schemas/SchemaPostMetricEdit' description: '' '400': content: application/json: schema: type: object properties: field_name: type: array items: type: string description: '' security: - api_key: [] components: schemas: PatchedSchemaPostMetricEdit: type: object properties: id: type: integer readOnly: true name: type: string description: Name of the metric description: type: string description: Description of what this metric evaluates audio_enabled: type: boolean description: Whether this metric evaluates audio content prompt: type: string description: The evaluation prompt used for this metric project: type: integer description: ID of the project this metric belongs to. agents: type: array items: type: integer description: >- List of agent IDs to enable this project-level metric for. Only applicable when project is set. assistant_id: type: string description: External identifier for the assistant type: enum: - basic - custom_prompt - custom_code - llm_judge type: string x-spec-enum-id: b44700c0a6443b40 description: >- Type of metric (`llm_judge` recommended; `basic` and `custom_prompt` are deprecated) * `basic` - Basic (Deprecated in favor of LLM Judge) * `custom_prompt` - Custom Prompt ( Deprecated in favor of LLM Judge) * `custom_code` - Custom Code * `llm_judge` - LLM Judge eval_type: enum: - binary_workflow_adherence - binary_qualitative - continuous_qualitative - numeric - enum type: string x-spec-enum-id: 1e3e27b342bfd8ec description: |- Output shape of the evaluation score * `binary_workflow_adherence` - Binary Workflow Adherence * `binary_qualitative` - Binary Qualitative * `continuous_qualitative` - Continuous Qualitative * `numeric` - Numeric * `enum` - Enum enum_values: type: array items: type: string description: >- Possible values for enum-type metrics (list of strings, e.g. ["resolved", "escalated", "abandoned"]) display_order: type: integer description: Order in which to display this metric in the UI configuration: type: object additionalProperties: {} description: >- Per-metric configuration. Some predefined metrics carry **per-agent** configuration, keyed by agent id: `configuration[] = {"": }`. On read, every agent attached to the metric is returned; on write, only the agent ids you include are updated. Call-level keys (not per-agent): * **Detect Silence** — `silence_duration` (int, seconds, default 10): minimum mutual silence before flagging a failure. * **Infrastructure Issues** — `infra_issues_timeout` (int, seconds, default 10): max seconds before the Main Agent must respond after the Testing Agent finishes speaking. Per-agent keys (each value is `{"": }`): * **Dropoff Node** — `nodes`: `{"": [{name, description}]}` — conversation stages used to classify where a call dropped off. * **Topic of Call** — `nodes`: `{"": [{name, description}]}` — topic categories used to classify each call. * **Pronunciation Check** — `pronunciation_words`: `{"": [[word, phonemes], ...]}` — how specific words should be pronounced (e.g. {"42": [["Cekura", "suh-KYUR-uh"]]}). * **Letterwise Pronunciation** — `spelling_word_types`: `{"": ["name", "email", ...]}` — word categories the Main Agent must spell out letter-by-letter. * **Hallucination** — `hallucination_kb_files`: `{"": [file_id, ...]}` — KnowledgeBaseFile IDs used as the source of truth for fact-checking. add_to_new_agents: type: - boolean - 'null' description: >- When enabled, this metric is automatically assigned to new agents created in the project. simulation_enabled: type: boolean description: |- Enable this metric for simulations. Example: `true` or `false` observability_enabled: type: boolean description: |- Enable this metric for observability. Example: `true` or `false` sampling_enabled: type: boolean description: Enable sampling for this metric using project-level sample rate evaluation_trigger: enum: - always - automatic - custom type: string x-spec-enum-id: ecd3c02e0e393ef5 default: always description: >- When to run this metric. * `always` — evaluate every call (default) * `automatic` — system decides based on call content * `custom` — only evaluate when `evaluation_trigger_prompt` condition is met * `always` - Always * `automatic` - Automatic * `custom` - Custom evaluation_trigger_prompt: type: string description: >- LLM prompt that decides whether to evaluate this call. Only used when `evaluation_trigger=custom` and `trigger_type=llm_judge`. Example: "Did the agent offer a refund?" trigger_type: enum: - llm_judge - custom_code type: string x-spec-enum-id: 2adad4b8df61914f default: llm_judge description: >- How to evaluate the trigger condition. Only relevant when `evaluation_trigger=custom`. * `llm_judge` — use `evaluation_trigger_prompt` (default) * `custom_code` — use `evaluation_trigger_custom_code` * `llm_judge` - LLM Judge * `custom_code` - Custom Code evaluation_trigger_custom_code: type: string description: >- Python code to evaluate the trigger condition. Only used when `evaluation_trigger=custom` and `trigger_type=custom_code`. custom_code: type: string description: >- Python code that implements the metric evaluation. Required when `type=custom_code`. Must define a function `evaluate(transcript, ...) -> bool | float | str`. SchemaPostMetricEdit: type: object properties: id: type: integer readOnly: true name: type: string description: Name of the metric description: type: string description: Description of what this metric evaluates audio_enabled: type: boolean description: Whether this metric evaluates audio content prompt: type: string description: The evaluation prompt used for this metric project: type: integer description: ID of the project this metric belongs to. agents: type: array items: type: integer description: >- List of agent IDs to enable this project-level metric for. Only applicable when project is set. assistant_id: type: string description: External identifier for the assistant type: enum: - basic - custom_prompt - custom_code - llm_judge type: string x-spec-enum-id: b44700c0a6443b40 description: >- Type of metric (`llm_judge` recommended; `basic` and `custom_prompt` are deprecated) * `basic` - Basic (Deprecated in favor of LLM Judge) * `custom_prompt` - Custom Prompt ( Deprecated in favor of LLM Judge) * `custom_code` - Custom Code * `llm_judge` - LLM Judge eval_type: enum: - binary_workflow_adherence - binary_qualitative - continuous_qualitative - numeric - enum type: string x-spec-enum-id: 1e3e27b342bfd8ec description: |- Output shape of the evaluation score * `binary_workflow_adherence` - Binary Workflow Adherence * `binary_qualitative` - Binary Qualitative * `continuous_qualitative` - Continuous Qualitative * `numeric` - Numeric * `enum` - Enum enum_values: type: array items: type: string description: >- Possible values for enum-type metrics (list of strings, e.g. ["resolved", "escalated", "abandoned"]) display_order: type: integer description: Order in which to display this metric in the UI configuration: type: object additionalProperties: {} description: >- Per-metric configuration. Some predefined metrics carry **per-agent** configuration, keyed by agent id: `configuration[] = {"": }`. On read, every agent attached to the metric is returned; on write, only the agent ids you include are updated. Call-level keys (not per-agent): * **Detect Silence** — `silence_duration` (int, seconds, default 10): minimum mutual silence before flagging a failure. * **Infrastructure Issues** — `infra_issues_timeout` (int, seconds, default 10): max seconds before the Main Agent must respond after the Testing Agent finishes speaking. Per-agent keys (each value is `{"": }`): * **Dropoff Node** — `nodes`: `{"": [{name, description}]}` — conversation stages used to classify where a call dropped off. * **Topic of Call** — `nodes`: `{"": [{name, description}]}` — topic categories used to classify each call. * **Pronunciation Check** — `pronunciation_words`: `{"": [[word, phonemes], ...]}` — how specific words should be pronounced (e.g. {"42": [["Cekura", "suh-KYUR-uh"]]}). * **Letterwise Pronunciation** — `spelling_word_types`: `{"": ["name", "email", ...]}` — word categories the Main Agent must spell out letter-by-letter. * **Hallucination** — `hallucination_kb_files`: `{"": [file_id, ...]}` — KnowledgeBaseFile IDs used as the source of truth for fact-checking. add_to_new_agents: type: - boolean - 'null' description: >- When enabled, this metric is automatically assigned to new agents created in the project. simulation_enabled: type: boolean description: |- Enable this metric for simulations. Example: `true` or `false` observability_enabled: type: boolean description: |- Enable this metric for observability. Example: `true` or `false` sampling_enabled: type: boolean description: Enable sampling for this metric using project-level sample rate evaluation_trigger: enum: - always - automatic - custom type: string x-spec-enum-id: ecd3c02e0e393ef5 default: always description: >- When to run this metric. * `always` — evaluate every call (default) * `automatic` — system decides based on call content * `custom` — only evaluate when `evaluation_trigger_prompt` condition is met * `always` - Always * `automatic` - Automatic * `custom` - Custom evaluation_trigger_prompt: type: string description: >- LLM prompt that decides whether to evaluate this call. Only used when `evaluation_trigger=custom` and `trigger_type=llm_judge`. Example: "Did the agent offer a refund?" trigger_type: enum: - llm_judge - custom_code type: string x-spec-enum-id: 2adad4b8df61914f default: llm_judge description: >- How to evaluate the trigger condition. Only relevant when `evaluation_trigger=custom`. * `llm_judge` — use `evaluation_trigger_prompt` (default) * `custom_code` — use `evaluation_trigger_custom_code` * `llm_judge` - LLM Judge * `custom_code` - Custom Code evaluation_trigger_custom_code: type: string description: >- Python code to evaluate the trigger condition. Only used when `evaluation_trigger=custom` and `trigger_type=custom_code`. custom_code: type: string description: >- Python code that implements the metric evaluation. Required when `type=custom_code`. Must define a function `evaluate(transcript, ...) -> bool | float | str`. required: - assistant_id - audio_enabled - configuration - description - display_order - eval_type - name - project - prompt - type securitySchemes: api_key: type: apiKey name: X-CEKURA-API-KEY in: header description: >- API Key Authentication. It should be included in the header of each request. ````