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Rate recalled memories

rate_recall

Label a specific recall's results as relevant or irrelevant so audit_memory can measure retrieval precision.

Instructions

Attach explicit relevance labels to one exact Pathmark recall so audit_memory can report measured precision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
recallIdYesThe recallId returned by chat or ask_memory.
relevantIdsNo
irrelevantIdsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.15

TDQS

C2.7/5.0
Behavior2/5

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

Annotations are all false (readOnlyHint false, destructiveHint false, etc.), so the description must carry behavioral disclosure. It implies a write operation (attaching labels) but doesn't explain side effects, reversibility, or response format. The link to audit_memory suggests downstream effects but lacks detail.

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?

The description is a single, compact sentence with no fluff. It front-loads the primary action. However, it could be structured to include more critical details without losing conciseness, such as clarifying the purpose of relevant/irrelevant IDs.

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 4 parameters, no output schema, and minimal annotations, the description is inadequate. It doesn't explain what a 'Pathmark recall' is, how relevantIds and irrelevantIds should be populated, or what the tool returns. An agent would struggle to invoke it correctly without additional context.

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 only 25% (only recallId has a description). The description does not explain note, relevantIds, or irrelevantIds beyond the vague 'relevance labels'. With low coverage, the description should compensate but doesn't, leaving agents guessing about parameter meaning and usage.

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?

The description states a specific action (attach relevance labels) on a specific resource (one exact Pathmark recall) and ties it to audit_memory's precision reporting. This is clear enough to understand the core function, though it doesn't explicitly differentiate from siblings like recall_memory or update_memory.

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 explicit guidance on when to use this tool versus alternatives. The mention of audit_memory implies a workflow but doesn't state when to choose rate_recall over other memory operations or what conditions warrant it. No exclusions or alternative tools are named.

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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