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NYCfoodie

by app.railway.up.nycfoodie-production
OverviewDiscussionsAdmin

submit_feedback

Record feedback on a tool result: a 1–5 rating, a comment, or both (at least one is required). Use after showing the user a recommendation to log what was good or wrong. Each call stores a new feedback entry; it changes nothing the user sees.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "submit_feedback"
  }
}

Input Schema

NameRequiredDescriptionDefault
toolNoWhich tool the feedback is about, e.g. 'search_restaurants'
ratingNo1 (poor) to 5 (excellent)
commentNoWhat was good or wrong

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations only mark the operation as non-read-only and non-idempotent. The description adds meaningful side-effect context: each call stores a new feedback entry and changes nothing the user sees, which aligns with and enriches the annotation hints.

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 short, information-dense sentences cover purpose, usage trigger, required content, and side effects with no filler. The essential constraint is front-loaded.

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 simple 3-parameter tool with no output schema, the description covers purpose, when to use it, side effects, and content rules. The main gap is the unclear requirement status of the 'tool' parameter and the absence of any success/return signal, but both are minor at this complexity level.

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

Parameters4/5

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

The schema already documents all three parameters, so the baseline is 3. The description adds the important validation rule that at least one of rating/comment is required, which the schema itself does not express. However, it leaves the 'tool' parameter's requirement ambiguous.

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 states a specific verb and resource: 'Record feedback on a tool result', and spells out the rating/comment fields plus the at-least-one constraint. This clearly distinguishes it from sibling tools that search, compare, or retrieve restaurant data.

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 it 'after showing the user a recommendation to log what was good or wrong,' which provides a clear trigger. It does not discuss exclusions or alternatives, but no sibling tool serves this feedback-logging purpose.

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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