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Glama

Energi Data Dk

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

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by detailing what the tool returns (top-N tools with names, descriptions, full schemas, and curated examples) and notes that results are 'ready to call directly, no second schema lookup needed.' This goes beyond annotations, though some details like pagination might be missing.

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 concise and front-loaded with the core purpose. It covers all essential aspects without unnecessary elaboration, efficiently using every sentence to convey purpose, usage, and output.

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, the description is complete. It explains the return value, usage context, and lists covered data domains. With no output schema, the description adequately informs the agent about what to expect.

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

Parameters4/5

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

Schema coverage is 100% with well-described parameters. The description adds value by clarifying that the tool accepts multiple aliases for the query (task, q, description, search) and provides examples in the input schema, reducing ambiguity for the agent.

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 verb 'Find tools' and specifies the resource: tools by describing the data or task. It distinguishes itself from sibling tools by indicating it should be called first to discover the option set, making purpose unambiguous.

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 provides explicit when-to-use guidance: 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available.' It does not explicitly list when not to use it, but the context is clear enough.

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

Several tools form overlapping clusters that are hard for an agent to distinguish: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, discover_tools, and suggest_questions all cover factual/research lookups, and the five Polymarket tools also overlap heavily. ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, making misselection essentially guaranteed in that pair. The descriptions are detailed, but the boundaries between many tools remain unclear at the set level.

Naming Consistency4/5

Almost all tool names are snake_case and mostly follow readable verb_noun or domain-specific patterns, such as ask_pipeworx*, resolve_entity, validate_claim, and polymarket_*. Minor deviations exist — bare verbs like remember/recall/forget/subscribe and noun-style names like spot_prices/co2_intensity — but there is no mixed casing and the overall pattern is predictable.

Tool Count2/5

34 tools is already over the 25+ threshold for a well-scoped server, and the mismatch is much worse because only three tools (co2_intensity, spot_prices, query_dataset) relate to the advertised Energi Data DK domain. The other 31 tools appear to belong to an unrelated general-purpose Pipeworx platform, so the count is not appropriate for the server's stated purpose.

Completeness3/5

For the stated Energi Data DK domain, energy data access is partially covered: two dedicated tools plus query_dataset as a generic escape hatch for all ~100 datasets prevents hard dead ends, but there are no typed tools for most of those datasets and no energy-specific monitoring/alerting. If the real intended domain is the broader Pipeworx platform, coverage is much stronger, but then the server name is misleading.

Resources