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liyexiaoyi

mnemosis-mcp

by liyexiaoyi

retrieval_quality

Compute retrieval quality metrics (average top score, retrievability, hit rate, weak rate) for queries to enable metacognitive monitoring of memory retrieval.

Instructions

Measure retrieval quality across queries: average top score, retrievability, hit rate and weak rate (metacognitive monitoring of retrieval, Koriat & Goldsmith 1996).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
top_kNo
queriesNo
Behavior2/5

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

With no annotations available, the description carries the full burden for behavioral disclosure. It only lists metrics and a citation; it does not state whether the tool executes queries, whether it is read-only, what the return format is, or any side effects or dependencies.

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, front-loaded sentence with no filler. The parenthetical reference to Koriat & Goldsmith is somewhat extraneous for an AI agent, but it does not bloat the text, and the overall structure is efficient.

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?

Given zero schema coverage, no annotations, and no output schema, the description is grossly incomplete. It lacks information about parameter usage, expected output, edge cases, or how this tool fits into the broader retrieval workflow, making it inadequate for correct invocation.

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%, and the description fails to explain any of the three parameters (limit, top_k, queries). The only implicit hint is 'across queries,' which vaguely alludes to the queries parameter but does not clarify its format or the roles of limit and top_k.

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 as measuring retrieval quality and enumerates specific metrics (average top score, retrievability, hit rate, weak rate). This distinguishes it from sibling tools that perform retrieval (e.g., search, recall) or general reporting (e.g., stats, practice_report).

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or exclusions, leaving the agent without context for selection among many sibling tools.

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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