Classify Odoo requirements into fit or gap buckets to identify which can be implemented natively and which need customization.
Classify Odoo requirements into fit/gap implementation buckets
| Name | Required | Description | Default |
|---|---|---|---|
| requirements | Yes | ||
| available_fields | No | ||
| available_models | No | ||
| business_context | No | ||
| installed_modules | No | ||
| use_live_metadata | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.3.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it's a safe, non-mutating operation. The description adds no further behavioral context, but with the annotations present, the baseline is acceptable. No contradiction observed.
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 a single sentence with no redundancy. Every word contributes to the purpose. It is efficiently front-loaded and concise.
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?
Despite having an output schema (not shown), the description fails to provide essential context about input format (e.g., what should 'requirements' look like), optional parameters' effect, or expected behavior when optional params are omitted. For a tool with 6 parameters and a specific analysis purpose, this is incomplete.
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%, meaning no parameter descriptions in the schema. The description does not elaborate on any parameter, including the required 'requirements'. Parameters like 'available_fields', 'available_models', and others have names that hint at meaning, but the agent gets no format, constraints, or examples. This is a critical gap.
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 action ('classify') and resource ('Odoo requirements'). It specifies the output as 'fit/gap implementation buckets', which is specific. However, it does not differentiate from siblings like 'data_quality_report' or 'upgrade_risk_report', which could also analyze requirements in different ways.
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 provided on when to use this tool versus alternatives. It does not mention prerequisites, context, or typical scenarios. The single-sentence description lacks any usage recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.