Server Quality Checklist

Tool Scores

• odoo_callA
  3.8/5.0
  Behavior2/5

  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 discloses that it uses named kwargs and runs one SQL transaction per call, but it does not mention potential data mutation, error handling, authentication requirements, or side effects. For a generic method caller, this is a significant gap.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two sentences with zero fluff. The main action (calling a method) is front-loaded, followed by the key request format and transaction detail. Every word earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a generic method-call tool with no output schema and no annotations, the description is too sparse. It does not explain the response format, error behavior, or how to construct complex params (e.g., domain, fields). The agent would have to infer too much from the schema alone, which is insufficient for a tool that can invoke arbitrary methods.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so baseline is 3. The description adds the note that only named kwargs (ids, context, plus params) are allowed, clarifying the relationship between parameters and going beyond the schema's individual descriptions. This raises the score to 4.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  States exactly what it does: calls one Odoo 19 External JSON-2 method via a specific HTTP endpoint. Clear verb+resource, and the sibling odoo_version is obviously different, so no ambiguity.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies this is the tool for making method calls, and the only sibling is odoo_version which serves a different purpose. However, it does not explicitly state when not to use this tool or mention alternatives, so it falls short of a 5.

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

• odoo_versionA
  4.5/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden. It discloses the HTTP method, the lack of API key requirement, and the expected response structure ({ version, version_info }). This is sufficient for a simple connectivity check, though it does not mention error behavior or idempotency, which are minor omissions for a GET endpoint.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, concise sentence that front-loads the endpoint, method, and purpose. Every word adds value, with no extraneous information.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a zero-parameter, read-only connectivity check, the description provides the endpoint, authentication requirement, and return fields. With no output schema, this is complete enough for an agent to invoke correctly. The low complexity means no additional context is needed.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  There are zero parameters, so the schema already fully covers parameter semantics (100% coverage vacuously). The baseline for 0 parameters is 4, and the description correctly omits any parameter-specific details since none exist.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states a specific verb (GET) and resource ({ODOO_URL}/web/version) with an explicit purpose of connectivity checking. It distinguishes from the sibling tool odoo_call by indicating this is a dedicated version/connectivity endpoint rather than a general call tool.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage for connectivity checks and indicates no API key is needed, which is helpful context. It does not explicitly state when not to use it or name alternatives, but the sibling odoo_call suggests a clear separation of concerns for version checks versus general calls.

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