memory_calibrar

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

With no annotations, the description carries the full burden. It hints that 'resolve' marks outcomes (a mutation of stored prediction state) and that the tool persists calibration data across calls, but it says nothing about permissions, reversibility of a resolve, or persistence scope. Useful but incomplete for a state-mutating feedback 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?

Two tight sentences with the purpose front-loaded after the alias tag, and no redundant restatement of the schema. Slightly diluted by the bracketed alias metadata, but otherwise efficient.

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 five-action tool with no output schema and no annotations, the description conveys the overall purpose but not the return shape of stats/trust/metrics or the effect of resolve. The schema covers action semantics, so nothing critical is missing, but the behavioral gaps remain.

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 coverage is 100% and every parameter (action enum, outcome, verify_id, limit) is already documented in the schema, so the description adds no syntax or format detail beyond it. Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific operations (track verify predictions, mark outcomes, compute P(correct|level)) and identifies the two siblings it bridges, faro verify and eco correct, so an agent can place it in the workflow. It is clear but the '[alias of cuba_calibrar]' prefix adds disambiguation noise rather than purpose detail, keeping it just short of 5.

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?

'Closes the feedback loop between faro verify and eco correct' implies the context in which this tool belongs, but there is no explicit when-to-use or when-not, and no statement of which action to pick. Usage is inferable rather than stated.

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