dataset_topThe highest (or lowest) rows of the The Water Hub dataset by a numeric column — "which is the most/least X".
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| column | Yes | ||
| ascending | No | true for the lowest first; default highest first |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only restates the ranking behavior and numeric-column requirement. It does not disclose tie handling, missing/null values, error behavior, or what fields are returned.
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 front-loaded sentence with the core ranking behavior first and an illustrative use case after. Minor grammatical awkwardness ('the The') does not obscure the meaning.
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?
For a simple 3-parameter read tool, the basics are inferable, but because there is no output schema and no annotations, the description should say more about the returned rows, default limit, and edge cases. It is minimally viable rather than complete.
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 schema documents only ascending; the description adds that column must be numeric and that highest/lowest corresponds to ordering. Limit semantics are left to the schema's numeric bounds, so the description only partially compensates for the 33% coverage.
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 states a clear operation: returning the highest or lowest rows of the dataset ordered by a numeric column. It is distinct from siblings such as dataset_stats, dataset_search, or dataset_row, though it does not name them.
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 quoted use case ('which is the most/least X') gives an implied context for ranking, but there is no explicit guidance about when to choose this tool over a search, stats, or single-row tool, nor any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation on the dataset or enquiry. dataset_search, dataset_row, dataset_compare, and dataset_top have clear differences in matching logic and output. Enquiry tools are clearly separate. No two tools appear to do the same thing.
All dataset tools follow a dataset_* pattern, and enquiry tools follow enquiry_* except submit_enquiry which inverts the order. This is a minor deviation but the overall naming is predictable and clear.
10 tools is well-scoped for the domain, covering both data querying and enquiry submission without bloat.
The dataset query surface covers schema, metadata, row lookup, search, stats, and top/bottom. Enquiry covers description, fields, and submission. Minor gaps like a 'list all rows' or enquiry status check exist but are not critical.