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Glama

Open Notify

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

A4.4/5.0
Behavior4/5

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

Adds context beyond annotations: pulls latest 10-K data, handles off-calendar fiscal years, sorts by primary metric, returns citation URIs. No contradiction with readOnlyHint or other 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?

Front-loaded with common user queries, then concise description. Every sentence adds value; no redundant information. Efficient single paragraph.

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

Completeness4/5

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

Covers types, data sources, entity count constraints, sorting, and citation output. Without output schema, the description adequately describes return format. Minor omission: no mention of error conditions or data freshness, but overall complete.

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%, so baseline is 3. Description adds meaning: explains enum values with concrete examples of data returned (revenue, net income for company; adverse-event counts for drug), and specifies tickers/CIKs vs drug names.

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 comparison of 2-5 companies or drugs, with specific verbs like 'compare' and 'rank'. It distinguishes from siblings like entity_profile by emphasizing parallel comparison 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 Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', and gives example queries. Implicitly suggests when not to use (single entity) but doesn't state alternatives explicitly; sibling list includes 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

A3.6/5.0
Disambiguation2/5

The three ask_pipeworx variants are near-identical (the beta is currently an exact copy of the stable router), and ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language questions to the same underlying source catalog. The six polymarket_* tools also heavily overlap in opportunity detection, though some clusters like memory and subscriptions are clearly separated.

Naming Consistency3/5

The naming is mostly snake_case but mixes conventions: verb_noun (list_subscriptions, resolve_entity), noun-first (entity_profile, bet_research), metadata-style prefixes (pipeworx_trending, polymarket_edges), and bare verbs (remember, recall, forget). It is readable but does not follow one predictable pattern across the set.

Tool Count2/5

33 tools is excessive for a server nominally named Open Notify, and the count is inflated by redundant ask_pipeworx variants and six closely-related Polymarket tools. The broad data-gateway scope could justify a large catalog, but the set feels bloated and unfocused rather than deliberately scaled.

Completeness2/5

For the apparent Open Notify domain, only astros and iss_now fit, and core ISS functionality like pass predictions is missing. The wider data-lookup surface is extensive, but the inclusion of unrelated memory, subscription, npm-scanning, and llms.txt tools means no single domain gets coherent lifecycle coverage.

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