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get_error_analytics

Read-onlyIdempotent

Track error-count time-series data with total and per-bucket counts for high-level error trends. Requires Portkey Enterprise; non-Enterprise plans return 403.

Instructions

Get error-count time-series data with summary.total_errors and per-bucket counts. Use this for high-level error trends; use get_error_rate_analytics for percentages, or get_error_status_codes_analytics and get_error_stacks_analytics for breakdowns. Enterprise-gated. Returns 403 on non-Enterprise Portkey plans.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configsNoLegacy Portkey query param for config slugs. Comma-separated string; prefer config_slugs for structured inputs.
span_idNoLegacy Portkey query param for span IDs. Comma-separated string; prefer span_ids for structured inputs.
cost_maxNoMaximum cost in cents to filter by
cost_minNoMinimum cost in cents to filter by
metadataNoLegacy Portkey query param for metadata filtering. Stringified JSON object, e.g. '{"env":"prod","app":"myapp"}'; prefer metadata_filter for structured inputs.
span_idsNoStructured alias for span_id. Use an array of span IDs; normalized to the legacy comma-separated Portkey query param.
trace_idNoLegacy Portkey query param for trace IDs. Comma-separated string; prefer trace_ids for structured inputs.
trace_idsNoStructured alias for trace_id. Use an array of trace IDs; normalized to the legacy comma-separated Portkey query param.
api_key_idsNoLegacy Portkey query param for API key UUIDs. Comma-separated string; request_analytics also accepts an array and normalizes it to this form.
prompt_slugNoFilter by prompt slug
status_codeNoLegacy Portkey query param for HTTP status codes. Comma-separated string; prefer status_codes for structured inputs.
ai_org_modelNoLegacy Portkey query param for provider/model pairs. Format: 'provider__model' with double underscore, e.g. 'openai__gpt-4' or 'anthropic__claude-3-opus'. Comma-separated string; prefer provider_models for structured inputs.
config_slugsNoStructured alias for configs. Use an array of config slugs; normalized to the legacy comma-separated Portkey query param.
status_codesNoStructured alias for status_code. Use an array of HTTP status codes; normalized to the legacy comma-separated Portkey query param.
virtual_keysNoLegacy Portkey query param for virtual key slugs. Comma-separated string; prefer virtual_key_slugs for structured inputs.
deployment_idNoComma-separated list of deployment IDs (UUIDs) to filter by. Prefer deployment_ids for structured inputs.
deployment_idsNoStructured alias for deployment_id. Use an array of deployment UUIDs; normalized to the comma-separated Portkey query param.
workspace_slugNoFilter by specific workspace
metadata_filterNoStructured alias for metadata. Use an object such as { env: 'prod' }; normalized to a JSON string before the request is sent.
provider_modelsNoStructured alias for ai_org_model. Use provider__model strings in an array; normalized to the legacy comma-separated Portkey query param.
total_units_maxNoMaximum number of total tokens to filter by
total_units_minNoMinimum number of total tokens to filter by
prompt_token_maxNoMaximum number of prompt tokens
prompt_token_minNoMinimum number of prompt tokens
virtual_key_slugsNoStructured alias for virtual_keys. Use an array of virtual key slugs; normalized to the legacy comma-separated Portkey query param.
completion_token_maxNoMaximum number of completion tokens
completion_token_minNoMinimum number of completion tokens
weighted_feedback_maxNoMaximum weighted feedback score (-10 to 10)
weighted_feedback_minNoMinimum weighted feedback score (-10 to 10)
time_of_generation_maxYesEnd time for the analytics period (ISO8601 format, e.g., '2024-02-01T00:00:00Z')
time_of_generation_minYesStart time for the analytics period (ISO8601 format, e.g., '2024-01-01T00:00:00Z')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether the tool call succeeded and returned structured data
dataNoStructured success payload when ok is true
errorNoStructured error payload when ok is false

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.13.0
    • addedInput schema / properties / deployment_id
      Added value: +{
+  "description": "Comma-separated list of deployment IDs (UUIDs) to filter by. Prefer deployment_ids for structured inputs.",
+  "type": "string"
+}
    • addedInput schema / properties / deployment_ids
      Added value: +{
+  "description": "Structured alias for deployment_id. Use an array of deployment UUIDs; normalized to the comma-separated Portkey query param.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  2. Changed16 schema fields changedv0.11.5
    • removedInput schema / properties / completion_token_max / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / completion_token_max / minimum
      Added value: +0
    • removedInput schema / properties / completion_token_min / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / completion_token_min / minimum
      Added value: +0
    • removedInput schema / properties / cost_max / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / cost_max / minimum
      Added value: +0
    • removedInput schema / properties / cost_min / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / cost_min / minimum
      Added value: +0
    • removedInput schema / properties / prompt_token_max / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / prompt_token_max / minimum
      Added value: +0
    • removedInput schema / properties / prompt_token_min / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / prompt_token_min / minimum
      Added value: +0
    • removedInput schema / properties / total_units_max / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / total_units_max / minimum
      Added value: +0
    • removedInput schema / properties / total_units_min / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / total_units_min / minimum
      Added value: +0
  3. Changed1 schema field changedv1.0.2
    • changedInput schema / required
      Previous value: -[
-  "time_of_generation_min",
-  "time_of_generation_max",
-  "api_key_ids"
-]New value: +[
+  "time_of_generation_min",
+  "time_of_generation_max"
+]
  4. Addedv1.0.1
  5. Removed
  6. First observed

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the read-only/idempotent/non-destructive profile, so the description's added value is the enterprise gating and the concrete failure mode ('Returns 403 on non-Enterprise Portkey plans') — genuinely actionable behavior an agent cannot get from structured fields. It stops short of describing bucket granularity or pagination/limits on the time series.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences: what it returns, when to use it vs. alternatives, and the gating constraint. Front-loaded with the core purpose and zero filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the enterprise gate plus sibling routing cover the main selection risks. Missing only operational detail such as time-range limits or bucket granularity for a 31-param time-series query.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% across 31 parameters, so the schema fully documents filters, legacy-vs-structured aliases, and formats. The description adds no parameter-level guidance (e.g., bucket size, allowed time-range width), so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Get error-count time-series data') and even previews the response shape (summary.total_errors, per-bucket counts). It explicitly distinguishes itself from three sibling analytics tools by name, so an agent can pick correctly without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit use case ('high-level error trends') and routes the agent to named alternatives for the adjacent needs: get_error_rate_analytics for percentages, get_error_status_codes_analytics and get_error_stacks_analytics for breakdowns. Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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