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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

A4.9/5.0
Behavior5/5

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

Annotations already mark it as read-only, open-world, idempotent. Description adds specifics: off-calendar fiscal year handling, sorting by primary metric, and output format (paired data + 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 lengthy but well-structured: opens with example triggers, then key directive, then details. Every sentence adds value; could be slightly trimmed but overall effective and front-loaded.

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's complexity (two entity types, specific data sources, sorting, output format), the description is comprehensive. No output schema exists, but description sufficiently explains return values (paired data + URIs).

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%. Description adds context to enum values ('company' pulls latest 10-K data, 'drug' pulls FAERS counts), explains array constraints (2-5 items), and provides examples. This significantly enhances schema descriptions.

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 it performs side-by-side comparison of 2-5 companies or drugs in a single parallel call, specifying data sources (SEC EDGAR/XBRL for companies, FAERS for drugs). It distinguishes from sibling tools like 'entity_profile' which handles single entities.

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 advises 'ALWAYS PREFER over sequential single-pack lookups' and provides example user queries. Implicitly indicates when not to use (fewer than 2 or more than 5 entities). States it replaces 8-15 sequential lookups.

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 ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded trio are functionally near-identical to an agent (the beta is explicitly described as currently identical to stable), and the five polymarket_* tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread) have heavily overlapping concerns around finding and validating prediction-market edges. The descriptions are detailed, but the boundaries require careful reading to pick correctly.

Naming Consistency4/5

All tools use snake_case and mostly follow a verb-first or noun-phrase convention, with recognizable family prefixes (ask_pipeworx_*, polymarket_*, pipeworx_*) that aid navigation. Minor deviations exist — bare nouns like categories and events, and the inconsistent verb placement in bet_research vs. validate_claim — but the overall pattern is predictable.

Tool Count1/5

33 tools is already heavy, but the fatal problem is that the server is named 'Nyc Parks' while ~31 of 33 tools are a generic Pipeworx data-retrieval/prediction-market toolkit. The count is egregiously mismatched to the stated purpose; only 2 tools relate to NYC Parks at all.

Completeness2/5

For the server's literal name, the surface is severely incomplete: categories and events exist, but there is no way to look up parks, facilities, permits, or event details, and no CRUD-lifecycle coverage. Viewed as a Pipeworx data toolkit the surface is quite thorough, but that is not what the server claims to be, so the stated NYC Parks domain is barely covered and creates dead ends.