memory_vigia

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the tool is read-only, what the return format is, whether it has side effects, or any performance characteristics—a significant gap for an analytics tool.

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

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

A single compact sentence with the alias note up front and zero waste. Every word is relevant, and the metric list is front-loaded.

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

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

With no annotations and no output schema, the description should carry more context about what the tool does (e.g., that it is read-only analytics) and what an agent can expect from each metric. It only names the metrics, leaving behavioral and return-value information entirely to inference.

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

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

Schema description coverage is 100%, and the enum descriptions fully explain each metric (counts, staleness, chi-squared, Leiden clustering, etc.). The tool description merely repeats the enum values, adding no meaning beyond what the schema already provides.

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

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

States the resource ('knowledge graph analytics') and lists the six metrics, and identifies the tool as an alias of cuba_vigia. That is clear enough to separate it from most siblings, though the description lacks a verb and does not explain what the analytics actually produce.

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

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

The description provides no when-to-use guidance, no prerequisites, and no alternatives. It simply lists the metric names, leaving the agent to infer usage from the schema enum descriptions.

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