cuba_calibrar

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

With no annotations, the description carries the whole burden. It usefully discloses a side effect — that trust scores are Beta(alpha,beta) credibilities 'updated by resolve outcomes' — and distinguishes read actions (stats/history/metrics) from write actions (resolve), but says nothing about permissions, persistence, or reversibility of resolve/trust updates.

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?

Two dense sentences, purpose first, relationship second, with no filler. Every clause carries information.

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 four-parameter, multi-action tool with no output schema and no annotations, the description adequately conveys the workflow and what metrics/trust represent. It stops short of describing result shapes for stats/metrics, but nothing critical for correct invocation is missing.

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 action enum already explains each mode, so the baseline is 3. The description adds little parameter detail beyond restating the calibration concept, though it does clarify the causal link between resolve and trust.

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 a specific verb+resource: track predictions, mark outcomes, compute P(correct|level), and names the calibration purpose explicitly. It is clear what the tool does, but it never distinguishes itself from its sibling memory_calibrar, which appears to be the same concept in a different namespace.

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 names the upstream/downstream relationship ('closes the feedback loop between faro verify and eco correct'), which implies when to use it, but gives no explicit when-to-use or when-not guidance and no distinction from memory_calibrar or cuba_eco.

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