classify_entity

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

With no annotations provided, the description fully covers behavioral traits: read-only and stateless (no side effects), authentication (none for basic, API key for pro), rate limits (free 10/day, pro unlimited), error handling (structured errors), idempotency, and data privacy. This is comprehensive and exceeds 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 and front-loaded with key information. However, it contains redundancy: the 'Behavior' paragraph and the 'Behavioral Transparency' section both mention read-only, stateless, rate limits, etc. This duplication adds unnecessary length. More concise organization would improve clarity.

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?

The description covers purpose, usage, and behavioral details thoroughly. It mentions return values (in-scope status, entity type, etc.), and since an output schema exists, that is sufficient. However, the parameter documentation is severely lacking, leaving a gap in understanding how to provide input. The description does not explain what 'description' means or provide examples, which is a notable omission.

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?

The input schema has two parameters with 0% coverage, so the description must compensate. However, the description merely repeats parameter names: 'description (str): The description to analyze or process.' This adds no semantic value and does not explain what kind of description is expected or how to format it, making it unhelpful for an agent.

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 a financial entity's DORA applicability + which entity type it is.' It lists specific outputs (in-scope status, entity type, proportionality tier, starting pillars), making the scope well-defined. However, it does not explicitly differentiate from sibling tools like classify_incident; the distinction is only implied by the tool name and context.

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 provides 'When to use' and 'When NOT to use' sections, offering some guidance (e.g., for gap analysis, not legal advice). It does not, however, compare this tool to siblings or specify when to prefer classify_entity over classify_incident or audit_pillar, leaving the agent to infer usage boundaries.

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