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

With no annotations, the description carries the full burden for behavioral disclosure. It discloses that it uses a local Gemma 4 LLM, implying non-deterministic output and possible resource use, and calls itself 'analysis,' suggesting read-only. However, it does not mention output format, limitations (e.g., text length), or whether any side effects occur, so it adds only modest behavioral context.

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 two sentences and every word earns its place. The first sentence defines what the tool does (AI-powered deep analysis against DORA Art. 30(2)) and the second explains how to supply input. No redundancy or fluff.

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?

Without an output schema, the description should explain what the tool returns, but it only says 'structured analysis' without specifics. It also does not mention practical limitations like text length limits or language constraints. Given the complexity of an LLM-based tool and the absence of annotations, the description is functional but leaves notable gaps.

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% with both parameters already described in the input schema. The description adds meaningful extra semantics by framing 'text' and 'contract_id' as alternatives ('Provide raw contract text or a contract_id'), implying mutual exclusivity. This goes beyond the schema's individual descriptions, so it deserves above baseline.

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 a specific verb ('deep analysis') and the resource ('contract text') against DORA Art. 30(2) mandatory clauses. It does not explicitly distinguish itself from sibling tools like clause_check or contract_gaps, but its focus on DORA Art. 30(2) and local Gemma 4 LLM makes its purpose clear and unique.

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 clear context on when to use this tool: when a deep, AI-powered analysis of contract text against DORA Art. 30(2) is needed. It gives input mode options ('raw contract text or contract_id') but does not exclude alternatives or state when not to use it, so it falls short of the explicit 'when-not' guidance required for a 5.

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