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Glama

Jpl Ssd

by io.github.pipeworx-io

What Can I Ask Pipeworx?

suggest_questions
Read-onlyIdempotent

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass topic (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional focus area: finance | pharma | economics | real-estate | betting | weather | government | science | news. Omit for a cross-category spread.

Schema Changelog

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

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds that it returns category-bucketed examples with exact tool+argument shapes from a live catalog, and that no-arg call gives full spread. 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?

Front-loaded with key phrases and synonyms. Lists categories and usage instructions efficiently. Slightly long but every sentence adds value.

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 no output schema, description fully explains return structure (category-bucketed example questions). Covers when to use, parameter behavior, and expected output. Annotations provide safety context. Complete for this simple tool.

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 has 100% coverage with one parameter (topic) described. Description adds concrete use cases, lists possible values (finance, pharma, etc.), and explains effect when omitted, exceeding schema detail.

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 explicitly states it returns category-bucketed example questions for onboarding, with clear verb ('returns') and resource ('example questions'). Distinguished from siblings by being the entry point, unlike ask_pipeworx or other specific tools.

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?

Directly instructs 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' Also explains how to use optional topic parameter for focus.

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

A3.5/5.0
Disambiguation2/5

Multiple tools overlap in purpose, especially the ask_pipeworx variants and the polymarket_* tools. An agent would struggle to distinguish between similar functions, increasing the risk of selecting the wrong tool.

Naming Consistency2/5

Tool names use inconsistent conventions: some are snake_case (close_approaches), some are verb_noun (generate_llms_txt), and others mix styles (ask_pipeworx vs. deep_research). No clear pattern is maintained across the set.

Tool Count1/5

At 35 tools, the server is bloated and unfocused. The majority of tools are unrelated to the 'Jpl Ssd' domain, which only has 4 relevant tools. The count is far too high for the stated purpose.

Completeness2/5

The JPL SSD coverage is minimal (only 4 tools), missing key functionalities like detailed object queries or bulk downloads. The remaining tools cover unrelated domains, so the surface is both incomplete for its primary domain and cluttered with off-topic tools.

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