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Glama

Timeapi Io

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"]).

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. Description adds rich behavioral details: data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), specific data points (revenue, net income, debt, adverse-event counts), sorting by primary metric, and citation URIs. This goes beyond annotations to define what the tool returns.

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?

The description is front-loaded with trigger phrases and efficiently covers both entity types. It is detailed but every sentence adds value; no fluff. Slightly long but justified by the tool's dual-purpose nature.

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

Completeness3/5

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

No output schema exists, so the description carries the burden. It explains what data is returned for each type and mentions sorting and citations, but lacks explicit output structure (e.g., JSON format). Adequate but could be more precise about the response shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description reiterates parameter meaning (tickers/CIKs for company, drug names) and provides examples, but adds minimal new semantic detail beyond the schema's own 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 comparisons of 2-5 companies or drugs, with trigger phrases like 'Compare X and Y' and 'which is bigger.' It distinguishes from sibling tools like entity_profile by advocating for parallel calls over sequential lookups.

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?

Explicit guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' Provides natural language examples and implies not to use for single entity queries, clearly differentiating from alternatives like entity_profile.

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

B3.2/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer natural-language data questions, and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The current_time* variants and multiple Polymarket scanners also create real selection ambiguity, though the memory and subscription tools are clearly distinct.

Naming Consistency3/5

Names are mostly lowercase snake_case and readable, but there is no consistent verb_noun pattern: some are imperative (ask_pipeworx, compare_entities, generate_llms_txt) while others are object-first (entity_profile, recent_changes, pipeworx_trending). Subfamilies like current_time* and polymarket_* are internally consistent, but the overall set follows no predictable convention.

Tool Count2/5

Forty tools is far too many for a server named Timeapi Io; only about nine tools actually relate to time zones and current time. The rest form a sprawling Pipeworx research, prediction-market, memory, and subscription platform, making this a mega-bundle rather than a well-scoped toolset.

Completeness3/5

The time-related surface covers current time, zone conversion, zone metadata, and ISO parsing, but lacks common date math or general formatting operations. The Pipeworx side is quite complete for research and fact-checking, but the mixed domain makes coverage uneven and hard to reason about as a single coherent service.

Resources