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Glama

Ssb No

by io.github.pipeworx-io

Table Meta

table_meta
Read-onlyIdempotent

Table definition (variables/dimensions and valid values). id is the numeric SSB table id, e.g. "07459".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesNumeric table id, e.g. "07459".

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: +[
+  {
+    "id": "07459"
+  }
+]
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior. The description adds context about what the output contains (variables/dimensions and valid values) and clarifies the 'id' as a numeric SSB table id, which is useful beyond the 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 a single sentence that is front-loaded with the core purpose and includes a clarifying example. Every word earns its place with no redundancy.

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?

This is a simple read-only lookup tool with one parameter, a fully descriptive schema, and rich annotations. The description explains the output nature and parameter semantics, making it complete for the tool's simplicity.

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% and already explains 'id' as a numeric table id. The description adds the 'SSB' qualifier and repeats the example, which is marginal value. Baseline 3 is appropriate given the schema carries the semantic weight.

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

Purpose4/5

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

The description states the tool provides 'Table definition (variables/dimensions and valid values)', which clearly identifies the resource and output. It lacks an explicit verb like 'retrieve' or 'get', but the noun phrase is unambiguous and distinguishes it from sibling tools like query_table.

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

Usage Guidelines3/5

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

Usage context is implied: use this tool when you need table metadata (schema) rather than actual data. No explicit when-to-use or alternatives are mentioned, but the resource type makes the intended use reasonably 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

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with detailed descriptions that explain when to use which. Overlapping tools like ask_pipeworx vs ask_pipeworx_grounded are explicitly differentiated by use case (casual vs high-stakes). The Polymarket tools are highly specialized and non-overlapping.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with descriptive terms (e.g., ask_pipeworx, resolve_entity, validate_claim). There is no mixing of camelCase or other conventions, making the names predictable and easy to parse.

Tool Count4/5

With 33 tools, the count is above the typical 3-15 range, but it is justified by the server's broad scope covering multiple domains (SEC, FDA, FRED, prediction markets, etc.) and includes meta-tools for discovery and monitoring. Each tool seems necessary for the overall functionality.

Completeness5/5

The tool surface covers a comprehensive range of operations: data querying, entity profiles, comparisons, monitoring, memory, search, and even feedback. It includes both general-purpose and specialized tools, leaving no obvious gaps for the stated purpose of authoritative data retrieval and analysis.

Resources