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

Annotations already cover read-only, idempotent and non-destructive semantics, but the description adds genuinely useful context: percentages are suppressed below n=30, the backtest is returned only if it was already computed, and the result is explicitly not live data. These are real behavioral traits beyond the annotations, though 'NFA' is left unexplained.

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 short and front-loads the metrics list, but it reads as compressed telegraphic fragments with unexplained acronyms ('NFA', 'moneda 50 %'), which trades clarity for brevity rather than earning conciseness.

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 output schema, the description must carry the return-value burden; it does list the metric components and the n<30 suppression rule, which is helpful, but it never describes the response shape, units, or how the metrics are grouped, leaving an agent guessing about what comes back.

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 single parameter 'horizonte' is documented in the schema (24, 72 or 168, default 24). The description adds nothing about the parameter, 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 what is computed (an auditable precision score with Brier, log-loss, 10 bins, Wilson, coin-flip baseline and persistence) plus a historical backtest, so the resource is identifiable. However it is written as a dense noun phrase of unexplained jargon in mixed Spanish/English and offers no differentiation from the temple_* siblings, so an agent cannot confidently distinguish its role.

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 call this tool versus any alternative, and no prerequisite or trigger conditions. The only constraints given ('Sin % públicos si n < 30', 'No es en vivo') are behavioral caveats, not usage guidance.

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