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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

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds behavioral details such as the return format (category-bucketed examples with exact tool+argument shape) and the ability to call with no arguments for a full spread. There is no contradiction 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 three sentences long, front-loaded with common queries, and packs substantial information without unnecessary fluff. Slightly verbose due to listing all categories, but generally 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 the tool has only one optional parameter, no output schema, and rich annotations, the description fully explains what the tool does, how to use it, and why. It covers the return value, usage patterns, and relationship to sibling tools, making it complete for the task.

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% (one optional parameter with description). The description adds that calling with no arguments gives a 'full spread' and that passing a topic focuses results. This adds some value but does not significantly extend the schema's clarity; 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 that the tool returns category-bucketed example questions for onboarding, using specific verbs like 'returns' and 'call'. It distinguishes itself from sibling tools by positioning as the entry point for new agents, saying 'Use this FIRST when you do not yet know what Pipeworx can do for you.'

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 usage guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools'. It names related tools (ask_pipeworx, entity_profile, etc.) but does not explicitly specify when not to use it, which is acceptable given the onboarding context.

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

A3.6/5.0
Disambiguation2/5

Several tools are near-duplicates by name and function, notably ask_pipeworx vs ask_pipeworx_beta, and the dense Polymarket family (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). Long descriptions help, but an agent cannot reliably pick between these without reading closely.

Naming Consistency4/5

Almost all names are lowercase_snake_case and mostly verb-leading (discover_tools, resolve_entity, unsubscribe), but there are noun-first exceptions (entity_profile, recent_changes, pipework_trending) and several phrasal or compound forms. This is a minor deviation from a clean verb_noun pattern rather than a chaotic mix.

Tool Count2/5

31 tools is over the heavy threshold, and the set feels bloated: multiple query routers, a half-dozen overlapping Polymarket tools, and two AI-visibility probes that could be merged. The count is especially hard to justify for a server named Tools 'OutLook Contacts', since none are contact management.

Completeness1/5

For the server's stated domain, Outlook Contacts, there are zero tools in that domain — no create contact, no list contacts, no update, no delete, no folders or mailboxes. Even though the actual Pipework toolkit is broad for its own domain, this set fails its declared intend domain entirely.