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Glama

Opensky

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.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate idempotent and read-only behavior. The description adds valuable behavioral detail: returns top-N most relevant tools with names, descriptions, and full input schemas, and that each result is ready to call directly. No contradictions with annotations.

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?

The description is well-structured, starting with the primary purpose and then providing usage context and output description. It is efficient, though could be slightly shorter.

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, the description compensates by explaining the return value (top-N tools with full schemas, ready to call). It covers purpose, usage, and output well for this complexity level.

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?

Input schema coverage is 100% with descriptions for all 6 parameters. The description mentions the main 'query' parameter and its aliases but does not add significant meaning beyond schema. Baseline 3 is appropriate.

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's purpose: 'Find tools by describing the data or task.' It uses specific verbs like browse, search, look up, discover and lists many example domains, making its function unambiguous. It also distinguishes itself from sibling tools by being a meta-tool for discovering others.

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 says 'Use when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST when you have many tools available.' This provides clear context for when to use the tool, though it does not explicitly list scenarios when not to use it.

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 have heavily overlapping entry points: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all take natural-language factual questions, and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. There is also overlap among get_states, get_aircraft, and airspace_activity, plus a large cluster of prediction-market tools with similar discovery purposes.

Naming Consistency4/5

The set is mostly snake_case and readable, with familiar patterns like get_*, list_*, resolve_*, and compare_*. It is not chaotic, but there are notable deviations: noun-phrase names like entity_profile, recent_changes, ai_visibility_check, and airspace_activity break the verb-first pattern.

Tool Count2/5

35 tools is too many for a single coherent server, especially because they comprise several independent families: aviation, data/research, prediction markets, memory, and subscriptions. Each tool is individually justified, but the bundle should be split into smaller focused MCP servers.

Completeness3/5

The data-research side is fairly complete, with discover, routing, grounded verification, entity resolution, search-within, compare, and follow-up tools, and the subscription and memory lifecycles are covered. However, the OpenSky side is incomplete: get_flights explicitly cannot return its data, and referenced route/arrival/departure tools are missing from the set.

Resources