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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

A4.6/5.0
Behavior5/5

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

Going beyond annotations (readOnlyHint, idempotentHint, etc.), the description reveals specifics: pulls latest 10-K from SEC EDGAR/XBRL for companies, handles off-calendar fiscal years, pulls FAERS data for drugs, sorts by primary metric, and returns citation URIs. 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?

Description is front-loaded with common usage phrases and is appropriately detailed. At 4-5 sentences, it is efficient but could be slightly more concise without losing information.

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?

For a tool with 2 parameters and no output schema, the description fully covers usage, parameter details, behavioral nuances, and return characteristics. No gaps identified.

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. Description adds meaning by explaining the data each type pulls (e.g., 'company pulls latest 10-K revenue...') and that values are tickers/CIKs or drug names with limits, enriching beyond schema.

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?

Description clearly states the tool performs side-by-side comparison of 2-5 companies or drugs, with specific verb phrases like 'Compare X and Y' and 'head to head'. It explicitly distinguishes itself from sequential single-pack 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?

The description provides strong guidance to 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', effectively telling when to use. It lacks explicit exclusions or listing of alternatives, but the context is clear.

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
Disambiguation3/5

Tools are mostly distinct but there is some overlap among lookup tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) and among Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage). Agents might occasionally struggle to choose the right one.

Naming Consistency2/5

Naming is inconsistent: some use verb_noun snake_case (ask_pipeworx, compare_entities), some are single words (forget, recall, remember), and others are noun-based (compliance_catalog, entity_profile). No consistent pattern.

Tool Count1/5

With 34 tools, the count is too high for a server named 'ISO Standards'. The majority of tools are unrelated to ISO standards (e.g., Polymarket, memory, web scraping), making the scope highly inappropriate.

Completeness1/5

As an ISO standards server, the tool set is severely incomplete. Only 4-5 tools (search_standards, get_standard, compliance_catalog, open_data_files) actually deal with ISO standards. Essential operations like comparing standards or browsing revisions are missing.