enquiry_fieldsEvery field of the HostingByStack enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 burden of behavioral disclosure. It clearly states what the tool returns (the fields with their properties), which is the key behavioral output. It does not explicitly mention that it is read-only or side-effect-free, but given the nature of the tool (listing fields) and the zero-parameter schema, this is implicitly safe. The description adds context about the output structure beyond what the empty schema provides.
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 two sentences: the first enumerates the content, the second provides usage guidance. It is concise, front-loaded with the essential information, and every sentence adds value. No fluff or redundancy.
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 tool with no parameters, no output schema, and a straightforward purpose (listing fields), the description is complete. It covers what the tool returns, the attributes included, and how to apply the results. The sibling tools are distinct, and nothing essential is missing for an agent to call this tool 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?
The tool has zero parameters, so the schema already covers everything (100% coverage). The baseline for 0 params is 4, and the description does not need to explain parameters. It does mention 'Pass answers to submit_enquiry keyed by field key,' which relates to a sibling tool rather than this tool's parameters, so it does not add parameter semantics beyond the baseline.
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: it lists every field of the HostingByStack enquiry, enumerating specific attributes (key, label, type, required, help text, options). This is a specific verb+resource (returns fields) and distinguishes it from siblings like submit_enquiry (which submits answers) and enquiry_describe (which likely describes the enquiry as a whole). It is not a tautology and provides concrete information.
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 gives a clear usage directive: 'Pass answers to submit_enquiry keyed by field key.' This tells the agent how to use the output, which is a practical guideline. It does not explicitly state when not to use this tool or mention alternatives, but the purpose is self-evident for retrieving field structure. The instruction adds value beyond a generic description.
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.
The dataset_* tools are mostly distinct, but dataset_row and dataset_compare overlap: both retrieve rows by matching a column value, and compare can effectively do row's job with a single value. The enquiry_* tools are clearly separated by behavior, fields, and submission.
Tool names consistently use lowercase snake_case with clear domain prefixes: dataset_* and enquiry_*. However, some names are nouns (dataset_columns, dataset_row, dataset_stats) while others are verbs or adjectives (dataset_compare, dataset_search, dataset_top), so the pattern is not perfectly uniform.
Ten tools is well-scoped for a server covering two clear areas: read-only dataset exploration and enquiry submission. Each tool has a practical role, and the count is comfortably within the ideal range.
The dataset side covers schema, provenance, exact lookup, substring search, comparisons, statistics, and top/bottom rows, which is strong for a read-only dataset server. The enquiry side covers describing the process, listing fields, and submitting with a two-step confirmation, though there is no way to check submission status or cancel an enquiry.