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Create feedback

portkey_create_feedback
Destructive

WRITES a feedback record into the Portkey account, attached to a request/trace by trace_id. Use for logging a quality score (typically -10..10) with an optional weight (0..1) and metadata. Portkey: POST /feedback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYesFeedback score, typically -10..10.
weightNoRelative weight of this feedback, 0..1.
metadataNoArbitrary metadata key/values.
trace_idYesThe request/trace id to attach feedback to.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The annotations only provide destructiveHint=true, so the description carries the burden of explaining how the mutation behaves. It adds that feedback is attached by trace_id, includes the quality-score semantics, and identifies the underlying HTTP POST endpoint. It does not discuss overwrite/idempotency or auth, but for a create operation this is sufficient additional behavioral context.

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?

Two short sentences plus an endpoint string, with the primary action 'WRITES' front-loaded. Every sentence carries meaning and there is no 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?

For a 4-parameter write operation with no output schema, the description gives the use case, parameter ranges, attachment mechanism, and the POST endpoint. It omits return-value details and error behavior, but this is a simple create action and the provided context is likely sufficient for correct invocation.

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 description coverage is 100%, so each parameter is already documented. The description repeats the value range (-10..10) and optional weight (0..1) and metadata, adding little beyond the schema; it slightly clarifies trace_id's role as the attachment target, but that is also in the schema.

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 opens with 'WRITES a feedback record into the Portkey account', naming a specific verb, resource, and attachment target. It clearly distinguishes this from all sibling get/list tools, which are read-only retrieval operations.

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

Usage Guidelines4/5

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

It explicitly says to use the tool 'for logging a quality score' with optional weight and metadata, which gives concrete invocation context. It does not explicitly name alternatives or exclusions, but the sibling set is entirely retrieval tools, so the intended use is clear enough.

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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TDQS

A3.9/5.0
Disambiguation5/5

Every tool targets a distinct resource or analytics operation; the list/get pairings are standard and clearly separated by resource type. No two tools appear to do the same thing.

Naming Consistency5/5

All tools follow a consistent portkey_<verb>_<resource> pattern using snake_case. The verbs are limited to list, get, and create, and the resource names are consistently ordered.

Tool Count4/5

Sixteen tools is slightly above the ideal 3-15 range, but each tool maps to a distinct resource or endpoint and none feel redundant. The count is manageable for an admin/observability server.

Completeness4/5

The read surface is strong: every major resource has list and get coverage, plus analytics and feedback logging. The main gap is the lack of create/update/delete operations for most managed resources, but for an inspection-focused tool this is a workable limitation.