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Expression Atlas

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"]).

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, FAERS), specific metrics fetched, fiscal year handling, and sorting behavior. Adds detail beyond annotations (readOnlyHint, etc.) without contradiction.

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?

Front-loaded with purpose and usage. Slightly verbose with example phrasings, but all sentences add value. Could be tightened without losing clarity.

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?

Covers inputs, data pulled, sorting, and output format (paired data + citation URIs) despite no output schema. Adequately prepares agent for correct invocation.

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 enriches both parameters: explains type enum values 'company' vs 'drug' with data details, and values parameter with ticker/name conventions and constraints.

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?

Explicitly states 'side-by-side comparison of 2–5 companies or drugs' with specific verb and resource. Distinguishes from sibling 'entity_profile' by framing it as a replacement for 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?

Clear directive: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' Provides example user intents and context, leaving no ambiguity about when to invoke.

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

A3.7/5.0
Disambiguation3/5

Many tools have overlapping purposes (e.g., multiple Polymarket tools, multiple company information tools), but descriptions help distinguish them. However, the variety of domains (brand monitoring, betting, package scanning, memory, etc.) can confuse an agent.

Naming Consistency2/5

Tool names have no consistent naming pattern: some are verb_noun (validate_claim), some are noun_verb (bet_research), some are compound (ai_visibility_check), and some are single word (forget). This makes it hard to predict tool names.

Tool Count2/5

28 tools is high, and the set spans many unrelated domains (brand visibility, SEC/FDA data, Polymarket, npm packages, memory, etc.) while the server is named 'Expression Atlas' with only 2 tools related to that purpose. The tool count feels excessive and unfocused.

Completeness1/5

For a server named 'Expression Atlas', only two tools (get_experiment, search_experiments) cover the domain. There are no tools for submitting, updating, or deleting experiments, nor any for data visualization. The surface is severely incomplete.

Resources