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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.

TDQS

A4.7/5.0
Behavior5/5

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

Adds rich behavioral detail beyond annotations: describes output structure (category-bucketed questions with exact tool+argument shape) and use cases. No contradiction with annotations (readOnly, idempotent, etc.).

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?

Well-structured but slightly verbose; front-loaded with trigger phrases. Every sentence adds value, but could be slightly more compact without losing clarity.

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, the description fully explains what is returned (categories, example questions, tool references). Sufficient for an agent to understand and use the tool.

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?

Schema coverage is 100%, and description adds significant value: explains the optional 'topic' parameter with examples and clarifies default behavior (full spread). No ambiguity.

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?

Clearly states it returns category-bucketed example questions with tool+argument shape, and distinguishes from siblings like ask_pipeworx by noting it's the onboarding entry point. Specific verb (suggest questions) and resource (what Pipeworx can do).

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?

Explicitly says to call with no arguments for full spread or with topic to focus, and advises using it first when unsure of capabilities. Does not explicitly list exclusions but context implies not for direct answers.

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

A3.8/5.0
Disambiguation2/5

The tool set mixes several distinct domains (satellite orbital data, Pipeworx data routing, prediction-market analysis, memory management, subscriptions), but within the Pipeworx umbrella there is heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language questions to the same underlying 5,756 tools. An agent could easily misselect between them, especially since ask_pipeworx and ask_pipeworx_beta are described as currently identical.

Naming Consistency3/5

Many tools follow a clear verb_noun pattern (list_subscriptions, create... none, but compare_entities, resolve_entity, generate_llms_txt, scan_dependency, subscribe/unsubscribe, remember/recall/forget), yet the naming is inconsistent across the set: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, get_satellite, get_group, recent_alerts, recent_changes, entity_profile, and deep_research do not share a uniform convention. CamelCase appears in polymarket_arbitrage, polymarket_edges, etc. while most others are snake_case, and the satellite tools (get_satellite, get_group, search_by_name) form a distinct sub-pattern that clashes with the Pipeworx meta-tools.

Tool Count2/5

34 tools is on the heavy side, and the effective surface is bloated: there are three variants of ask_pipeworx, four polymarket_* tools, three satellite-specific tools that are unrelated to the server's apparent core purpose, and several meta/utility tools (remember, recall, forget, pipeworx_feedback, pipeworx_trending, suggest_questions) that could be consolidated or are only tangentially related. The count itself is not extreme, but the scope is muddled: the server claims the name Celestrak (satellite tracking) while the overwhelming majority of tools are for Pipeworx data access and prediction markets, making the tool count feel inappropriate for either purpose.

Completeness3/5

For the Pipeworx data-access domain, the tool set is quite thorough: natural-language routing, grounded answers, deep research, entity profiling, entity comparison, claim verification, semantic search, and tool discovery are all present. However, there are notable gaps: the subscription lifecycle lacks an update/resume mechanism, and the satellite domain (the server's namesake) is severely incomplete — only three lookup tools with no live tracking, no group listing beyond a handful of groups, and no clear lifecycle CRUD. The memory tools (remember/recall/forget) are minimal but complete for their narrow scope.