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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

A4.9/5.0
Behavior5/5

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

Discloses data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), handling of off-calendar fiscal years, and citation URIs. Annotations (readOnlyHint, etc.) are already positive; description adds valuable behavioral context without contradiction.

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?

Every sentence adds value, but the description is a dense block of text. Could be slightly more structured with line breaks, but no wasted words.

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 no output schema, the description mentions return type ('paired data + citation URIs'), covers edge cases (off-calendar fiscal years), and is sufficient for a 2-parameter comparison tool.

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 has 100% coverage with descriptions for both parameters. Description enhances by specifying the exact financial metrics for company type and count types for drug type, and confirms min/max items.

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 performs side-by-side comparisons of 2–5 companies or drugs, using examples of user queries. It distinguishes from siblings like entity_profile by specifying the multi-entity comparison scope.

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 when comparing entities,' providing clear when-to-use guidance. Also implies when not to use (e.g., single entity lookup).

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
Disambiguation4/5

Most tools have clearly distinct purposes, though there is some overlap between `ai_visibility_check` and `scan_competitor_ai_presence`, and between `bet_research` and `polymarket_edges`. Overall, an agent can distinguish them.

Naming Consistency3/5

Tool names follow snake_case but vary in prefix usage (e.g., `pipeworx_*`, `polymarket_*`, no prefix) and verb presence (e.g., `discover_tools` vs. `generate_llms_txt`). The pattern is readable but inconsistent.

Tool Count2/5

With 24 tools, the server is overloaded for the 'Prayer Times' name. Many tools are unrelated to prayer, suggesting poor scoping relative to the server's implied purpose.

Completeness2/5

For prayer times, the server includes core tools but lacks features like multi-day forecasts or advanced settings. However, the inclusion of many unrelated tools makes the set incoherent and incomplete for any single domain.