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Glama

Isbn

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

A4.6/5.0
Behavior5/5

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

Annotations indicate readOnly, idempotent, and non-destructive. The description adds detailed behavioral context: data sources (SEC EDGAR/XBRL for companies, FAERS/FDA for drugs), handling of off-calendar fiscal years, sorted results by primary metric, and inclusion of 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?

The description is a single coherent block with an efficient opening pattern of example commands. Every sentence adds value, but it could be slightly more scannable with bullet points. Still concise given the information density.

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 tool with two entity types, multiple data sources, and sorting behavior, the description covers all essential aspects: data retrieval, scope, sorting, and output format. No output schema is provided, but the description adequately describes the return structure (paired data + URIs).

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%, setting baseline at 3. The description enriches both parameters: explains 'type' enum values and the expected format for 'values' (tickers/CIKs for companies, drug names). It also details the data pulled per entity type, adding significant value beyond schema 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 the tool performs side-by-side comparisons of 2-5 companies or drugs, listing specific metrics and sources. It distinguishes itself from sibling tools like entity_profile, which likely provides single-entity details.

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?

The description explicitly recommends using this tool over sequential single-entity lookups for comparisons. It defines when to use (comparing companies/drugs) but does not explicitly state when not to use, though it's implied.

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 (entity_profile, compare_entities, ask_pipeworx, etc.). However, ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very similar, and suggest_questions/discover_tools overlap slightly. Overall, tools are well-disambiguated with only minor ambiguity.

Naming Consistency3/5

All tool names use snake_case, but the pattern is inconsistent: some start with a verb (ask_, validate_), others with a noun (entity_, bet_). Several are noun_noun (entity_profile), and some are single verbs (remember). No consistent verb_noun pattern across the set.

Tool Count2/5

33 tools is excessive for a server named 'Isbn' that only has 2 ISBN-specific tools. The majority are from Pipeworx, creating scope mismatch. Multiple redundant tools (three ask_pipeworx variants, several polymarket tools) inflate the count unnecessarily.

Completeness2/5

For a server named 'Isbn', completeness is very low—only conversion and validation are provided; no metadata lookup or other ISBN-related features exist. The Pipeworx tools themselves are comprehensive, but they do not align with the server's implied domain.

Resources