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Glama

Destatis

by io.github.pipeworx-io

Destatis Table

destatis_table
Read-onlyIdempotent

Fetch a Destatis GENESIS statistical table's data by its code (get codes from destatis_search), e.g. "12411-0001" (population) or "61111-0001" (consumer price index). Returns the table content (values across its dimensions) plus title. Germany-wide and by Land where the table provides it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyNoOptional — your own free Destatis GENESIS API token. Omit to use the shared Pipeworx token.
table_codeYesGENESIS table code, e.g. "12411-0001".

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: +[
+  {
+    "_apiKey": "your-destatis-api-key",
+    "table_code": "12411-0001"
+  },
+  {
+    "_apiKey": "your-destatis-api-key",
+    "table_code": "61111-0001"
+  }
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context about returning table content (values across dimensions) plus title, and indicates data scope (Germany-wide and by Land where provided), which goes 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?

Three concise sentences: action, examples, output description. Information is front-loaded and every sentence serves a clear purpose 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?

Given the tool's simplicity, full schema coverage, and good annotations, the description covers all necessary aspects: what it does, required input, output format (table content and title), and data scope. No output schema exists, so covering return value is appropriate and done well.

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

Parameters5/5

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

Schema coverage is 100% (both parameters documented). The description adds value by providing real-world examples, emphasizing that table_code comes from destatis_search, and clarifying that _apiKey is optional. This enriches the schema information.

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 the tool fetches Destatis GENESIS table data by code, provides concrete examples ("12411-0001", "61111-0001"), and distinguishes it from the sibling destatis_search tool by directing users to obtain codes from there.

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 explicitly mentions using destatis_search to get table codes, giving clear context for when to use this tool. While it doesn't state when not to use it, the guidance is sufficient for correct invocation.

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

A3.9/5.0
Disambiguation2/5

The ask_pipeworx family—ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded—plus deep_research all describe the same router under slightly different modes, and the six polymarket tools overlap heavily around edge detection and arbitrage. ai_visibility_check and scan_competitor_ai_presence are also near-duplicates, so agents will frequently have to choose between tools that appear to do the same thing.

Naming Consistency3/5

All names use snake_case and several families share prefixes (ask_pipeworx, polymarket_, pipeworx_, destatis_), which helps discoverability. However the pattern is not consistent: bare verbs (remember, recall, forget), adjective_noun phrases (recent_alerts, recent_changes), and noun_noun names (entity_profile, bet_research) are all mixed.

Tool Count2/5

With 33 tools, the surface is well past the 25+ threshold and mixes unrelated concerns: Destatis statistics, a general data router, prediction-market analytics, memory, and AI-marketing scans. The count could be justified if split into separate servers, but as one set it feels over-stuffed.

Completeness4/5

For the broad data-retrieval/research purpose the descriptions reveal, coverage is strong: lookup, grounded answers, validation, entity resolution, comparison, change feeds, subscriptions, memory, and Destatis search/table are all present. The only notable weakness is that the Destatis-specific surface is just search-and-fetch, which is thin for a server literally named Destatis, but this is offset by the general router.

Resources