classify_entity

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

With no annotations provided, the description fully covers behavioral aspects: it declares read-only, stateless, idempotent, no side effects, authentication requirements (free vs. pro), rate limits (10/day free), error handling (structured errors), and data privacy. This is exceptionally thorough and goes well beyond basic expectations.

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?

The description is well-structured with clear sections (Behaviors, When to use, Args, Behavioral Transparency). It is front-loaded with the core purpose. However, there is some repetition (e.g., 'Behavior' and 'Behavioral Transparency' overlap) and the Args section could be omitted if schema descriptions were sufficient.

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?

Given the tool has 6 parameters and no output schema shown, the description provides adequate context: it explains the return values (first reporting FY, report year, ESRS standards), behavioral transparency, usage guidelines. Missing elements include differentiation from sibling tools and more concrete parameter semantics, but overall it is fairly complete.

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 0% (no descriptions in schema), so the description must compensate. The Args section provides one-line descriptions for each parameter, but they are vague and uninformative (e.g., 'The employees to analyze or process' for all parameters). No clarification on how values affect classification or constraints, leaving significant gaps.

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 clearly states the tool's purpose: 'Classify when the entity must first report under CSRD.' It specifies the verb 'classify' and the resource 'when the entity must first report under CSRD', and mentions the outputs (first reporting FY, report year, ESRS standards). This clearly distinguishes it from sibling tools like double_materiality_assessment or ghg_emissions_readiness.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing clear guidance on appropriate contexts (e.g., gap analysis, readiness checks) and explicitly warns against using as legal advice. However, it does not mention alternative tools from the same server for similar tasks, which would further enhance guidance.

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