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Glama

Singstat Sg

by io.github.pipeworx-io

Table Data

table_data
Read-onlyIdempotent

Fetch the time-series data rows for a Singapore statistics table by resourceId (get ids from search_tables). Data is returned under Data with a row array of series, each containing dated columns. Filter time periods with timeFilter (comma-separated periods like "2020,2021") or between (a from,to range like "2010,2020"); page with offset/limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax number of rows to return.
offsetNoNumber of rows to skip (pagination).
sortByNoSort expression, e.g. "rowtext asc".
betweenNoInclusive period range "from,to", e.g. "2010,2020".
resourceIdYesTable id from search_tables, e.g. "M810001".
timeFilterNoComma-separated specific periods to return, e.g. "2020,2021,2022".
seriesNoORrowNoNoComma-separated series/row numbers to limit which series are returned.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "resourceId": "M810001"
+  },
+  {
+    "limit": 10,
+    "resourceId": "M810001",
+    "timeFilter": "2020,2021,2022"
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by detailing the return structure (Data with row array of series containing dated columns). No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences: first sentence gives core purpose and data structure, second explains filtering, third covers pagination. It is front-loaded and concise with no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description explains the return format (Data with row array of series containing dated columns). It covers filtering and pagination. Parameter count is 7 but required only 1, and schema provides descriptions. The description is sufficient for correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all parameters are described in the schema. The description mentions timeFilter and between specifically but does not add substantial meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches time-series data rows for a Singapore statistics table by resourceId, distinguishing it from sibling tools like search_tables (which retrieves IDs) and table_metadata (likely metadata). It also describes the returned data structure.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use (after getting resourceId from search_tables) and how to filter time periods with timeFilter or between and paginate with offset/limit. It does not explicitly state when not to use or provide alternatives, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.1/5.0
Disambiguation5/5

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.

Naming Consistency3/5

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.

Tool Count3/5

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.

Completeness3/5

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).

Resources