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Notion_connect

by io.github.pipeworx-io

Compare Entities

compare_entities
Read-onlyIdempotent

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type: "company" or "drug".
valuesYesFor company: 2–5 tickers/CIKs (e.g., ["AAPL","MSFT"]). For drug: 2–5 names (e.g., ["ozempic","mounjaro"]).

TDQS

A4.6/5.0
Behavior5/5

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

Annotations provide readOnly, openWorld, idempotent hints. Description adds significant behavioral detail: data sources (SEC EDGAR for companies, FAERS for drugs), handling of off-calendar fiscal years, sorting by primary metric, and return of pipeworx:// citation URIs. 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?

Description is front-loaded with example queries, then technical details. It is dense but clear and efficient, with no wasted words. Slight room for better structuring of technical vs. usage info.

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?

No output schema, but description explains return format (paired data + citation URIs). Covers the complexity of two entity types, data sources, and sorting. Complete for the tool's scope.

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 coverage is 100% with descriptions for both parameters. The description adds context: for 'values' it explains tickers for company and names for drug, and constraints like 2-5 items. Enhances schema without repeating.

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 specifies the verb 'compare' and resources 'companies or drugs' with explicit examples like 'X vs Y' and 'head to head'. It distinguishes itself from siblings like entity_profile by stating it replaces sequential single-entity lookups.

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?

Provides explicit usage preference: 'ALWAYS PREFER over sequential single-pack lookups.' Mentions example queries but does not explicitly state when not to use (e.g., for single entity), though it is implied.

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.

Resources