list-paged-model

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: the tool is read-only ('retrieves'), sanitizes data ('remove circular dependencies and excessive data'), supports pagination ('paginated view'), and allows filtering. It could improve by mentioning performance implications or error handling, but it covers essential operational aspects well.

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 front-loaded with the core purpose in the first sentence, followed by supporting details in clear, concise sentences. Each sentence adds value: data sanitization, filtering logic, and usage context, with no redundant or vague phrasing.

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's complexity (3 parameters with nested objects, no output schema, and no annotations), the description is mostly complete. It explains the tool's purpose, behavior, and usage context effectively. However, it lacks details on return format or error cases, which would be helpful for programmatic use without an output 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?

The schema description coverage is 100%, providing detailed documentation for all parameters (page, page_size, filter). The description adds minimal value beyond the schema, only implying filtering capabilities ('allows to filter based on multiple criteria') without specifying how they map to parameters. This meets the baseline for high schema coverage.

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 with specific verbs ('retrieves', 'provides access') and resources ('cells (vertices and edges) in the current Draw.io diagram'). It distinguishes itself from siblings by emphasizing pagination, filtering, and sanitized data access, unlike tools that modify or select specific cells.

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 for usage ('useful for programmatic inspection of diagram structure without overwhelming response sizes'), implying this tool is for read-only analysis rather than modification. However, it does not explicitly state when to use alternatives like 'get-selected-cell' for single-cell access or when not to use it (e.g., for real-time updates).

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