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LogicMem

LogicMem MCP Server

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by LogicMem

logicmem_memory_reflect

Evaluate a draft answer by comparing it with relevant memories, using a question and optional memory query to guide self-critique.

Instructions

Self-critique: evaluate a draft answer against retrieved memories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes
draft_answerYes
memory_queryNo
Behavior1/5

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

Behavioral transparency is very low. The description does not disclose whether the tool has side effects, is read-only, or what exactly 'evaluate' entails (e.g., returns score, critique text). Since no annotations are present, the description must bear the full burden, and it fails to provide sufficient behavioral insight.

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

Conciseness3/5

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

The description is very concise, consisting of a single sentence. However, it could be more informative without significant added length. It is not overly long, but the lack of detail reduces its effectiveness.

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

Completeness1/5

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

This tool has 3 parameters, no output schema, and no annotations. The description is insufficient to fully understand the tool's behavior and expected inputs. It lacks context about the evaluation process, return format, and potential side effects.

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?

The description gives a hint that draft_answer is the answer to evaluate and that memories are involved, but it does not explicitly map parameters to their roles. The memory_query parameter is not explained at all. With 0% schema coverage, the description should compensate but does not.

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 clearly states the tool's function: evaluating a draft answer against retrieved memories. It specifies the verb 'evaluate' and the resources 'draft answer' and 'retrieved memories'. This helps distinguish from sibling tools like logicmem_memory_log or logicmem_memory_recall, which have different purposes.

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

Usage Guidelines1/5

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

No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it give any context about prerequisites or typical workflow.

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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