MCP Odoo Bridge Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return format ('List of fields with their types and descriptions'), which adds some context, but lacks details on permissions, error handling, rate limits, or whether it's a read-only operation. For a tool with zero annotation coverage, this is insufficient to fully inform agent behavior.

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 appropriately sized and front-loaded, starting with a clear purpose statement. The 'Args' and 'Returns' sections are structured efficiently, with no wasted words. Every sentence adds value, making it easy to scan and understand quickly.

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 moderate complexity (2 parameters, no annotations, but has an output schema), the description is partially complete. It covers the purpose and parameters well, and the output schema likely details return values, reducing the need for that in the description. However, it lacks behavioral context like error cases or usage scenarios, leaving gaps for an agent to operate effectively.

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 description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'model' is 'The Odoo model name' and 'field_types' is an 'Optional list of types to filter (e.g., ['many2one', 'char'])', including examples. This compensates well for the schema's lack of descriptions, though it doesn't cover all possible parameter nuances like format constraints.

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: 'Get field definitions for an Odoo model.' It specifies the verb ('Get') and resource ('field definitions for an Odoo model'), making the function understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_models' or 'get_record', which might also involve model metadata or retrieval, so it misses the highest score for sibling distinction.

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 no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like needing field metadata for validation, form building, or data mapping, nor does it reference sibling tools like 'list_models' (which might list models) or 'get_record' (which retrieves actual data). Without such context, users must infer usage from the purpose alone.

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