MCP Odoo Server

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 mentions pagination via 'limit' and 'offset' and filtering by 'year', which adds some context. However, it lacks details on permissions, rate limits, error handling, or whether the operation is read-only (implied by 'List' but not confirmed). This is inadequate for a tool with multiple parameters and no annotation coverage.

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 the core purpose followed by parameter details. Every sentence earns its place by clarifying inputs and outputs. It could be slightly more concise by integrating parameter explanations more seamlessly, but overall it's efficient and well-structured.

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 (4 parameters, no annotations, but with an output schema), the description is fairly complete. It covers the purpose, parameters, and return value ('List of public holidays'). The output schema handles return details, so the description doesn't need to explain those. However, it lacks behavioral context like error cases or usage scenarios, which holds it back from a perfect score.

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 significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'calendar_id' as 'Working calendar ID', 'year' for filtering, 'limit' for maximum entries, and 'offset' for pagination. This compensates well for the schema's lack of descriptions, though it doesn't detail data formats or constraints (e.g., valid year ranges).

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: 'List public holidays (global time off) from a working calendar.' It specifies the verb ('List'), resource ('public holidays'), and source ('working calendar'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'list_leave_allocations' or 'list_leave_types', which prevents a perfect score.

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 sibling tools like 'create_public_holiday' for adding holidays or other list tools for different data types. Usage is implied by the name and purpose but not explicitly stated, leaving gaps for an AI agent.

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