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capture_reviewer_feedback

Record a human reviewer's decision on an evaluation, including comments and corrected verdict, for later retrieval and tracking.

Instructions

Record a human reviewer's decision on an evaluation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "evaluation_id": "<evaluation_id>",
      "reviewer_name": "<reviewer_name>",
      "decision": "<decision>"
    },
    "name": "capture_reviewer_feedback"
  }
}

Input Schema

Name	Required	Description	Default
`comments`	No
`decision`	Yes
`evaluation_id`	Yes
`reviewer_name`	Yes
`corrected_verdict`	No

Output Schema

Name	Required	Description	Default
`status`	Yes
`feedback_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 17, 2026

TDQS

C2.6/5.0

Behavior2/5

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

No annotations, so the description carries full behavioral burden. It implies a write/persist operation but doesn't say whether entries are immutable, whether duplicates are allowed, whether the reviewer must be authorized, or what happens on conflicting decisions. An output schema exists, so return values needn't be explained, but the mutation semantics are undisclosed.

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?

Single sentence, front-loaded with the verb and resource, no filler. Efficient but so terse that it omits necessary detail rather than being genuinely well-structured.

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

Completeness2/5

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

A mutation tool with 5 params, 0% schema coverage, no annotations. The output schema covers returns, but the description doesn't compensate for the parameter and behavioral gaps. An agent cannot reliably determine what 'decision' values are valid or what 'corrected_verdict' means without guessing.

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

Parameters1/5

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

Schema description coverage is 0% across 5 parameters. The description mentions none of them specifically — not evaluation_id, decision format, reviewer_name, comments, or corrected_verdict. With zero coverage and no compensating text, meaning is left entirely to bare param titles.

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?

Specific verb 'Record' plus resource 'human reviewer's decision on an evaluation', which is clearly distinguishable from siblings like lookup_evaluation_result or search_documents. It doesn't name siblings explicitly but the purpose is unambiguous.

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

Usage Guidelines2/5

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

No indication of when this should be used versus alternatives like lookup_evaluation_result, no prerequisites, no mention of whether the evaluation must exist already. Usage is only implied by the verb 'Record'.

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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