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Glama

Usgs Earthquakes

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

A4.9/5.0
Behavior5/5

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

Discloses data sources (SEC EDGAR/XBRL for company financials, FAERS/FDA for drugs), handles off-calendar fiscal years with examples (AAPL Sep, NVDA Jan), explains results are sorted by primary metric, and mentions returns paired data with citation URIs. This significantly exceeds the readOnly and idempotent annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with trigger phrases and a clear purpose statement, then packs essential behavioral details (fiscal years, sorting, data sources) without rambling. Every sentence contributes meaningful guidance; no filler or redundancy.

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 read-only comparison tool with no output schema, it fully explains returns (paired data + citation URIs), data repositories, sorting behavior, and entity-type specifics. It also notes the efficiency win (replaces 8–15 sequential lookups), making it contextually complete for an agent.

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?

The schema already provides 100% coverage with descriptions of type and values, including min/max and example formats. The description adds extra examples (AAPL, MSFT, ozempic, mounjaro) and explains what data each type pulls, enriching parameter meaning beyond the basic 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?

The description opens with clear trigger phrases and states 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call,' providing a specific verb and resource. It distinguishes itself from sequential single-pack lookups and sibling tools like entity_profile by emphasizing the batch comparison nature.

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?

It explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and lists concrete user phrasing ('X vs Y', 'which is bigger', 'rank these companies', 'head to head'). This gives clear when-to-use guidance and directs away from inferior alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Usgs Earthquakes toolsInspect
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TDQS

A3.6/5.0
Disambiguation1/5

The tool set is dominated by tools unrelated to USGS earthquakes (e.g., Polymarket betting, company profiles, memory operations). An agent would find it nearly impossible to distinguish the few earthquake-specific tools from the multitude of unrelated ones, leading to severe misselection.

Naming Consistency3/5

Most tool names follow a verb_noun pattern with underscores (e.g., search_earthquakes, count_earthquakes), which is consistent. However, the variety of verbs and domains creates a sense of incoherence, and some tool names are overly generic (e.g., process, run) in the broader context, though those are not present here. The naming pattern is acceptable but the inconsistency in domain scope reduces clarity.

Tool Count1/5

With 29 tools but only 3 directly related to earthquakes, the tool count is grossly inappropriate. The server's name suggests a focused purpose, but the vast majority of tools belong to other domains (e.g., Pipeworx queries, Polymarket betting, company data). This extreme mismatch makes the tool set bloated and misleading.

Completeness2/5

For earthquake data, the server provides only search, count, and get by ID. Missing are common operations like listing recent quakes, subscribing to alerts, or updating/correcting data. The coverage is minimal and insufficient for a comprehensive earthquake tool server, leaving significant gaps that agents could not work around.

Resources