validate_financial_model

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

No annotations exist, so the description carries the full burden. It reveals that the tool performs validation (affecting a model?) but does not say if it mutates anything, returns detailed errors, or is read-only. There is no disclosure of side effects, failure behavior, or what 'basic model consistency' concretely checks. It is not contradictory, just insufficient.

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 one short sentence, so it is concise, but it is also under-specified. It front-loads the verb but the content is too vague to be useful. Conciseness without information earns a middle score.

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?

For a tool with a single undocumented object parameter and no annotations, the description is far from complete. The output schema exists, which could clarify return values, but the essential validation rules are missing. An agent cannot know what inputs are acceptable or what output to expect beyond a generic schema.

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 0%, and the only parameter is a nested object with additionalProperties true and no inner schema. The description says 'model' is checked but does not explain the expected shape, keys, or constraints. Since the schema provides almost no meaning for the parameter, the description needed to compensate but did not.

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 says the tool validates required fields, numeric values, and basic model consistency, but omits what specific checks are performed or what 'model' means. It does distinguish this from its siblings (get_* tools are data-retrieval: fetch financial statements and metrics. This tool does validation, so the verb is distinct, but 'model' is ambiguous and the validation scope is under-specified. It is a tautology-level explanation: 'validate' + 'model' is near the tool name.

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?

No guidance is given on when to use this tool versus the sibling tools. It does not say 'use after building a model' or 'use before project_financials'. With zero context about prerequisites, ordering, or alternatives, an agent can't decide when to invoke it. No exclusions or alternative names are mentioned.

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