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nexo_cognitive_metrics

Analyze cognitive performance metrics including retrieval relevance, error rates, and multilingual recommendations to monitor and improve AI agent memory systems.

Instructions

Performance metrics: retrieval relevance %, repeat error rate, multilingual recommendation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions metrics but does not disclose behavioral traits such as whether this is a read-only operation, requires authentication, has rate limits, or affects system state. The description is minimal and lacks critical operational context for a tool that likely reports data.

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 concise with a single phrase listing metrics, which is front-loaded and wastes no words. However, it is under-specified rather than efficiently informative, slightly reducing its effectiveness. It avoids redundancy but could benefit from more complete information.

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

Completeness3/5

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

Given the tool has an output schema (which should cover return values), no annotations, and low parameter complexity, the description is minimally adequate but incomplete. It lists metrics but fails to explain the tool's action, usage, or behavioral aspects, leaving gaps in understanding despite the output schema handling return values.

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

Parameters3/5

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

Schema description coverage is 0%, but there is only one parameter ('days') with a default value. The description does not mention parameters at all, so it adds no meaning beyond the schema. However, with 0 parameters documented in the schema and a simple single parameter, the baseline is 3 as the schema provides basic structure without semantic details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Performance metrics: retrieval relevance %, repeat error rate, multilingual recommendation' lists specific metrics but lacks a clear verb and resource. It states what metrics are provided but not what action the tool performs (e.g., 'retrieve' or 'calculate'). It distinguishes from siblings by focusing on cognitive metrics, but the purpose remains vague without an explicit action.

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 guidance is provided on when to use this tool versus alternatives. The description lists metrics but does not specify context, prerequisites, or exclusions. Sibling tools like 'nexo_cognitive_stats' or 'nexo_cognitive_inspect' might overlap, but no differentiation is offered, leaving usage unclear.

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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