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Glama

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"]).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only/idempotent hints. Description adds that data comes from external APIs (SEC EDGAR, FAERS), handles off-calendar fiscal years correctly, and results are sorted by primary metric. 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 trigger phrases and each sentence adds value. Slightly verbose but still efficient. Could be trimmed without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but the description explains return format (paired data + citation URIs) and sorting. For a comparison tool with two parameters and external data sources, this is fairly complete.

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 enriches by detailing what each type pulls (company: financials; drug: FAERS counts) and provides examples for values (tickers, drug names).

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 specifies side-by-side comparison of 2-5 entities (companies or drugs), cites specific data sources (SEC EDGAR, FAERS), and states result sorting. Clearly distinguishes from sibling tools like entity_profile.

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 states when to use: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and that it replaces 8-15 lookups. Provides example triggers and explains type-specific behavior.

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
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, and deep_research all answering questions, and bet_research overlapping with polymarket_edges/arbitrage. The diverse tool set lacks clear boundaries.

Naming Consistency3/5

All names use snake_case, but verb patterns are inconsistent: some start with verbs (ask_pipeworx, remember) while others start with nouns (polymarket_arbitrage, entity_profile). Names vary widely in length and descriptiveness.

Tool Count2/5

33 tools is excessive for a server named 'Omdb', which implies a movie database. Most tools are unrelated to movies, indicating poor scoping for the server's purpose.

Completeness2/5

For the OMDb domain, only search and retrieval tools exist, with no create/update/delete operations. Overall, the tool set feels like a random collection with significant gaps relative to any coherent domain.