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Glama

Destatis

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already include readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds context: returns top-N most relevant tools with full schemas and examples, ready to call directly, no second lookup needed. No contradictions.

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

Conciseness4/5

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

Two sentences, front-loaded with purpose, no wasted words. Could be slightly more structured but very efficient.

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 6 params (with many aliases), no output schema, the description covers purpose, usage, return format (top-N with full schemas and examples), and guidance to call first. No gaps for an agent to use correctly.

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 coverage is 100%, baseline 3. Description mentions aliases for query but mostly repeats schema info. Does not add significant new meaning beyond what's in the schema property descriptions.

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 finds tools by describing data or task, lists many domains (SEC filings, FDA drugs, etc.), and distinguishes itself from sibling tools as a discovery meta-tool.

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

Usage Guidelines5/5

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

Explicitly says 'Use when you need to browse, search, look up, or discover what tools exist for:' and 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' Provides clear when-to-use and alternatives implied.

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

All Destatis toolsInspect
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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