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Glama

Estat Japan

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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, but the description adds rich behavioral context: it explains data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), handling of off-calendar fiscal years, sorting by primary metric, and 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 reasonably concise given the amount of useful information. Front-loads trigger phrases, then provides technical details. Every sentence adds value, but it could be slightly tighter. Still well-structured and readable.

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?

With only 2 parameters, no output schema, and good annotations, the description fully covers what the tool does: data pulled, sorting, citation URIs, and the fact it replaces many sequential lookups. No gaps remain for the agent to use it correctly.

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 coverage is 100%, but description adds significant meaning beyond short schema descriptions. It explains that type='company' pulls latest 10-K financials and type='drug' pulls adverse-event counts, approval counts, and clinical trials. It also clarifies values: for companies, tickers/CIKs; for drugs, drug names. This greatly aids parameter selection.

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 explicitly states it performs side-by-side comparison of 2-5 companies or drugs, with trigger phrases like 'compare X and Y', 'X vs Y', and 'head to head'. It distinguishes from siblings by noting it replaces 8-15 sequential single-entity lookups, making the purpose clear and unique.

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?

Description includes strong guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It provides examples of when to use (e.g., 'which is bigger', 'rank these companies'). While it doesn't explicitly state when not to use, the guidance is sufficient for correct selection among siblings.

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

Many tools have overlapping purposes, especially the ask_pipeworx variants and Polymarket tools, but detailed descriptions help differentiate. Some tools like 'discover_tools' and 'suggest_questions' also have similar discovery roles, causing potential confusion.

Naming Consistency3/5

Names follow snake_case but lack a consistent pattern: some start with verbs (e.g., 'ask_pipeworx', 'compare_entities'), others with nouns (e.g., 'entity_profile', 'recent_changes'), and prefixes like 'pipeworx_' and 'polymarket_' are used sporadically, making the naming scheme mixed but still readable.

Tool Count2/5

35 tools is excessive for a server named 'Estat Japan', which should focus on Japanese statistics. The majority of tools are general-purpose Pipeworx tools, diluting the scope and making the count feel bloated for the stated purpose.

Completeness2/5

The e-Stat tools (list_data_catalog, search_stats, get_metadata, get_data) provide basic read-only access but lack update or delete operations. The inclusion of many unrelated tools leaves significant gaps for Japanese statistics, and the overall surface is incomplete for the server's implied domain.

Resources