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memory_submit_response

Submit your response after retrieving team memory to enable faithfulness evaluation, verifying that your answer used the recalled knowledge.

Instructions

Submit your response text after using memory_recall results. This enables faithfulness evaluation — measuring whether your response was based on the retrieved knowledge. Call this AFTER you've used memory_recall results to answer a question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
projectNo
responseYes
result_idsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses the evaluation purpose and dependency on memory_recall, but does not state side effects, whether it stores/overwrites data, permissions, or error conditions. Adequate but shallow.

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?

Two sentences with minimal fluff. The timing is repeated ('after using memory_recall results' appears twice), so there is slight redundancy, but each sentence adds distinct value: action and purpose.

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?

For a tool with two required and two optional parameters, the description does not explain how to populate query or result_ids, nor the role of project. Output schema exists, so return values are covered, but the input contract is incomplete.

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%, so the description must compensate. It hints at 'response text' (response) and 'memory_recall results' (likely result_ids) but does not explain query or project, leaving required and optional parameters 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, resource, and context: submit response text after using memory_recall results. It names the exact prior tool and the evaluation purpose, clearly distinguishing it from siblings like memory_recall or memory_save.

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 'Call this AFTER you've used memory_recall results to answer a question,' giving a clear temporal trigger. It does not mention when not to use or alternatives, but the workflow context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.