cuba_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 never says whether the metrics are read-only, computationally expensive (Leiden clustering and betweenness centrality are heavy), whether they mutate graph state, or what latency to expect.

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?

It is a single short line, which is efficient, but roughly half its content is a bare enumeration that duplicates the enum values already present in the schema. It is under-specified rather than truly concise.

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?

The sole input parameter is fully documented by the schema, so the input side is covered. With no output schema and no annotations, the description leaves the return shape and operational cost of these analytics unstated, which is a real gap for a multi-mode analytics tool.

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's per-value descriptions are far richer than the description text (e.g. 'Leiden clustering', 'harmonic + closeness centrality + k-core ranking'). The description merely restates the enum keys, adding no meaning beyond the schema, so the baseline 3 applies.

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?

The description names the domain (knowledge graph analytics) and lists the six metric modes, so an agent can tell roughly what kind of tool this is. However, it is a noun fragment with no verb and no indication of what the tool actually returns or does with the graph, and it does not differentiate this from sibling analytics/supervision tools like cuba_centinela or cuba_calibrar.

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?

There is no statement of when to reach for this tool versus alternatives, no prerequisites, and no mention of the large family of cuba_* siblings that perform adjacent analyses. The agent must infer usage entirely from the metric names.

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