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get_user_requests_analytics

Read-onlyIdempotent

Retrieves per-user request-count time-series data to identify heavy users and traffic concentration. Enterprise plan required.

Instructions

Get per-user request-count time-series data with counts grouped by user. Use this to find heavy users and traffic concentration; use get_users_analytics for aggregate active and new user trends instead. Enterprise-gated. Returns 403 on non-Enterprise Portkey plans.

Input Schema

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

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
Behavior4/5

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

Annotations already declare readOnlyHint=true and no destructive behavior. The description adds value by noting that the tool is Enterprise-gated and returns 403 on non-Enterprise plans, which is essential behavioral context beyond annotations. However, it does not detail other behavioral aspects like pagination or output format, but the presence of an output schema mitigates that need.

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?

The description is three sentences, each earning its place: first for purpose, second for usage guidelines, third for access restrictions. No fluff, front-loaded with the core action.

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?

Given the complexity (29 parameters, required fields, output schema exists), the description covers purpose, usage guidelines, and a key behavioral constraint (Enterprise gating). It does not describe the output schema or pagination, but the presence of an output schema and rich parameter descriptions in the schema partially compensate. Slight gap in not mentioning that time range and api_key_ids are required, but the schema 'required' field handles that.

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?

The input schema has 100% description coverage, so each parameter is already documented. The tool's description adds no additional parameter-level meaning beyond what the schema provides. Per guidelines, baseline 3 is appropriate when schema coverage is high.

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?

The description clearly states it retrieves per-user request-count time-series data grouped by user. It uses a specific verb ('Get') and resource, and distinguishes from the sibling tool 'get_users_analytics' by naming the alternative.

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?

The description explicitly provides when to use this tool ('find heavy users and traffic concentration') and when to use the alternative ('get_users_analytics for aggregate active and new user trends'). It also warns about the Enterprise-gated restriction and 403 response, giving clear usage constraints.

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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