table_metadataGet the structure/metadata for a Singapore statistics table by resourceId (get ids from search_tables): theme, subject, frequency, period coverage and the list of variables/series. Result is under Data.records.
| Name | Required | Description | Default |
|---|---|---|---|
| resourceId | Yes | Table id from search_tables, e.g. "M810001". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "resourceId": "M810001"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive. The description adds behavioral detail: the result location under 'Data.records' and the specific fields returned (theme, subject, frequency, period coverage, variables/series). This adds value beyond annotations, though it could mention error handling or data limits.
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?
Two concise sentences. The first sentence captures the core purpose and required input, the second tells where to find the result. No superfluous words, well-structured.
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?
Given the tool's simplicity (1 parameter, no output schema, but rich annotations), the description is fairly complete. It lists the types of metadata returned and the location. Missing details like data format or pagination, but these are minor for such a tool.
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 100% for the sole parameter 'resourceId', with a clear description and example. The tool description repeats the example but does not add new semantic information. Baseline 3 is appropriate given high schema 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 clearly states the verb 'Get' and the resource 'structure/metadata for a Singapore statistics table'. It also tells how to obtain the required resourceId from the sibling tool 'search_tables', making the purpose unambiguous.
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?
Explicitly instructs to 'get ids from search_tables', which tells the agent when to use this tool (after obtaining a resourceId). It does not explicitly state when not to use, but the context is clear. A more detailed exclusion would improve it further.
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 has a clearly defined purpose with detailed descriptions, and despite some composite tools, there is no ambiguity in when to use which one.
Tool names mix verb_noun and noun_noun patterns, with some purely verb names, lacking a consistent convention. While readable, the pattern is not predictable.
With 23 tools, the server is on the heavy side for a mixed-purpose toolset. Each tool earns its place, but the count feels slightly bloated for the breadth of domains covered.
The server covers several domains (AI visibility, betting, entity lookup, etc.) with reasonable depth, but the lack of a unified domain means some areas feel under-served (e.g., no update/delete except memory).