Aggregate any OpenDataSoft dataset's records using SQL expressions like count, sum, avg, group by, filter, or sort to answer quantitative queries.
Run an OpenDataSoft Explore v2.1 aggregate query on any dataset.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| where | No | ||
| select | Yes | Aggregate select expression, e.g. "count(*)", "sum(population)", "avg(value)". | |
| dataset | Yes | ||
| group_by | No | ||
| order_by | No | ||
| portal_url | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description must disclose behavioral traits. It only states that it runs an aggregate query, which is an action but does not mention side effects, authentication needs, rate limits, or what the response contains. There is no mention of output format or potential limitations, leaving the agent with minimal behavioral insight.
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, compact sentence that front-loads the key purpose ('aggregate query'). It is concise and free of fluff, but it sacrifices essential detail. Structure is adequate for a short definition, though the brevity reduces overall value.
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?
This is a complex tool with 7 parameters, no output schema, and no annotations. The description provides almost no context for how to construct an aggregate query (e.g., how group_by interacts with select, what where filtering supports, or what the returned data looks like). It is far from complete for an agent to call it correctly.
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 only 14% (only 'select' has a description). The tool description does not compensate for the lack of explanation for portal_url, dataset, group_by, order_by, where, and limit. No parameter semantics are added beyond what the schema barely provides, so an agent cannot understand the role of most parameters.
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 a specific action ('Run an OpenDataSoft Explore v2.1 aggregate query') on a resource ('any dataset'). The term 'aggregate' distinguishes it from the sibling tool query_records, which likely handles plain queries, but it does not explicitly name that alternative. It is specific enough to understand the tool's function.
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?
There is no guidance on when to use this tool versus alternatives like query_records or inspect_dataset. It only states that it runs aggregate queries, which implies a use case but provides no exclusions, prerequisites, or context to help an agent decide between siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.