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Notion_connect

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.

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already mark it as read-only, open-world, idempotent, and non-destructive. The description adds value by detailing return content and default behavior, but does not cover potential limitations like rate limits.

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 concise but front-loaded with key terms; it packs substantial information into a single paragraph without being verbose.

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?

Despite no output schema, the description adequately explains the return value (category-bucketed examples with tool details), covers multiple invocation patterns, and addresses the target audience.

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% with parameter description. The description enriches by listing specific topic values (finance, pharma, etc.) and explaining how omission changes behavior.

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 returns category-bucketed example questions with exact tool+argument shapes, and positions it as an onboarding entry point for new users.

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?

Explicitly says 'Use this FIRST when you do not yet know what Pipeworx can do for you' and explains when to pass a topic vs. omit it, providing clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Notion_connect toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same 5,708 tools, with beta explicitly described as currently identical to the stable version. Prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage) also blur together, and the Notion tools are a small island in a sea of unrelated Pipeworx utilities.

Naming Consistency3/5

The names are uniformly lowercase with underscores, but conventions are mixed: some use verb-first patterns (ask_pipeworx, generate_llms_txt, scan_dependency), others are noun-phrases (entity_profile, recent_changes, polymarket_edges), and domain prefixes are inconsistent (notion_*, polymarket_*, pipeworx_*, but bare bet_research, compare_entities, recall). It is readable but lacks a coherent naming scheme.

Tool Count2/5

36 tools is already heavy, but the bigger issue is scope: the server is named Notion_connect yet only 5 of 36 tools relate to Notion. The rest span data research, prediction markets, memory, subscriptions, AI visibility, npm auditing, and llms.txt generation — a grab bag far beyond any single purpose, with multiple redundant meta-tools inflating the count.

Completeness2/5

As a Notion connector it is severely incomplete: there is no create/update/delete for pages or databases, and no way to write content back to Notion — only read/search/query operations. For the broader Pipeworx surface, the tool set is sprawling but unfocused, so it is hard to identify a coherent domain where coverage could be considered complete.

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