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

With no annotations supplied, the description carries the full burden and does well: it discloses third-party egress to api.typesafe.ai, admits a quantified false-negative rate rather than overselling, and frames the output as non-authoritative probabilities. It omits operational details such as authentication, rate limits, latency, or cost, which keeps it short of a 5 for a no-annotation 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?

Purpose and the sibling contrast are front-loaded, then the two warnings follow in descending importance, which is the right order. It runs long and the measured-statistics sentence could be tightened, but nearly every sentence adds decision-relevant information rather than filler.

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?

For a probabilistic judgment tool with network egress and no annotations, the definition covers purpose, alternatives, accuracy limits, and privacy risk, and an output schema exists so return values need not be explained. The gaps are real: the `language` parameter is unaddressed, and the description invokes a stance/threshold mechanism without saying how a caller supplies or influences it.

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 0%, so the description must compensate, and it largely does not: `code` is only alluded to as 'el fragmento' and the `language` parameter is never mentioned at all. It also references a 'stance' and threshold selection that have no corresponding parameter in the schema, leaving the agent unsure how that mechanism is controlled.

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 opening states the resource (a code fragment) and what comes back (a probability per rule), and the second paragraph explicitly contrasts it with `review_code`: here the corpus judges, there you judge. The phrase 'opinión del corpus' is slightly metaphorical, but combined with the sibling contrast an agent can tell the two apart without opening either schema.

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?

It gives explicit when-to-use (order what to review first and say which rule), explicit when-NOT-to-use (not a gate, do not wire it into CI, with measured evidence of 38% of violations passing), and an explicit alternative for the privacy case (use `review_code` if the code cannot leave the machine). Nothing is left for the agent to infer.

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