Estadísticas del banco

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: repeated questions across exams are counted once, and it explicitly excludes returning questions or answers.

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 compact sentences: the counting behavior and grouping dimensions come first, followed by the deduplication rule and the negative scope. No 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?

An output schema exists, so return shape need not be explained, and the description covers counting scope, dedup semantics, and exclusions. The unexplained 'año' grouping versus the two-parameter schema is the only residual gap.

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%, so both parameters are fully documented in the schema and the description only mirrors that (especialidad triggers a per-tema breakdown). It also mentions grouping 'por año' although no year parameter exists, which adds mild ambiguity rather than clarity.

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 ('Cuenta') and resource ('preguntas del banco') plus the grouping dimensions (curso, especialidad, año, tema). An agent can tell this is an aggregate-count tool, distinct from buscar_preguntas or generar_simulacro, though no sibling is named explicitly.

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?

Usage is only implied: 'No devuelve preguntas ni respuestas' signals that question retrieval belongs to buscar_preguntas, and the optional-especialidad rule is conveyed. There is no explicit when-to-use or when-not-to-use statement referencing alternatives.

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