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Glama

Ipma Pt

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

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns top-N most relevant tools with names, descriptions, and full input schemas, and that results are 'ready to call directly, no second schema lookup needed.' No contradiction. Provides behavioral insights beyond 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?

Single paragraph of three concise sentences. First sentence states core purpose and examples. Second sentence describes output and value. Third sentence provides usage guidance. No redundant information. Every sentence earns its place.

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

Completeness4/5

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

Despite no output schema, description adequately covers what the tool returns: 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly.' It also mentions limit parameter behavior. However, it could be more specific about the exact JSON structure of the output.

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?

All 6 parameters have descriptions in the input schema (100% coverage). Description adds value by listing alias parameters (task, q, description, search) and explaining that the 'query' field accepts natural language with examples. This helps the agent understand how to use the parameters correctly.

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?

Description uses specific verbs like 'find', 'browse', 'search', 'look up', and 'discover' to clearly state the tool's purpose. It lists a broad range of domains (SEC filings, financials, FDA drugs, etc.) and distinguishes itself from sibling domain-specific tools as a meta-tool for discovering which tool to use.

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 states when to use: 'Call this FIRST when you have many tools available and want to see the option set'. Also provides context: 'Use when you need to browse, search, look up, or discover what tools exist for:' followed by examples. Implicitly advises against using for a single answer by saying 'not just one answer'.

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 / ask_pipeworx_beta / ask_pipeworx_grounded / deep_research cluster overlaps heavily on question-routing, and the six polymarket_* tools all operate on prediction-market edges and can be confused. The ipma_*, memory, and subscription tools are distinct, but the overlapping clusters create real misselection risk.

Naming Consistency3/5

Snake_case is used throughout and there are clear prefix groups (ipma_*, ask_pipeworx, polymarket_*), but the rest mix verb-first (compare_entities, discover_tools), noun-first (entity_profile, bet_research), and bare verbs (remember, recall, forget). Readable overall, but no consistent verb_noun convention.

Tool Count2/5

36 tools is heavy, and the server name 'Ipma Pt' implies a narrow Portugal-weather service while 31 of the tools belong to a broad Pipeworx data/prediction-market platform. The scope mismatch makes the count feel bloated rather than curated.

Completeness4/5

The dominant Pipeworx domain is well covered: querying, grounded answers, deep research, entity resolution, comparison, claim validation, subscriptions, memory, and tool discovery are all present with few dead ends. Minor gaps exist (e.g., no general web search tool, thin IPMA historical/warning coverage), but agents can work around them.

Resources