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submit_agent_feedback

Submit bounded private operational telemetry after a concrete posterly workflow outcome. This is non-destructive to product content but writes a private feedback event. Never include API keys, prompts, captions, media URLs, personal data, or fabricated outcomes. Requires an authenticated bearer API key and paid API add-on.

Input Schema

NameRequiredDescriptionDefault
toolYes
clientNo
sourceYes
commentNo
contextNo
outcomeYes
error_codeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, and the description reinforces this by clarifying it is 'non-destructive to product content but writes a private feedback event'. It also adds genuinely new behavioral context the annotations lack: bearer-key auth, a paid add-on requirement, and explicit privacy prohibitions (API keys, prompts, captions, media URLs, personal data, fabricated outcomes).

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

Conciseness4/5

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

Four sentences, front-loaded with the purpose, and each carries a distinct piece of information (purpose, safety, privacy, auth). Slightly dense but no wasted filler and structure is scannable.

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

Completeness3/5

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

With no output schema and only narrow annotations, the description carries much of the burden, and it does cover safety, auth, and privacy well. But for a 7-parameter tool with a nested object and no schema descriptions, it omits any parameter-level guidance, leaving the agent to guess at field semantics.

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

Parameters2/5

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

Schema description coverage is 0% across 7 parameters, yet the description names none of them. It never explains source, tool, outcome enums, the nested context object (attempt, latency_ms, request_id, http_status), comment, client, or error_code, so it does not compensate for the complete absence of schema-level param documentation.

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

Purpose4/5

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

States a specific verb and resource ('Submit ... operational telemetry') and scopes it to 'after a concrete posterly workflow outcome'. It implicitly separates itself from the sibling submit_product_feedback by framing this as operational rather than product feedback, but never names or contrasts that sibling explicitly.

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

Usage Guidelines3/5

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

Gives triggering context ('after a concrete posterly workflow outcome') and constraints on what to include, which is implied usage guidance. However, it never says when to choose this over the very similar submit_product_feedback, nor when not to use it, leaving the key routing decision 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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