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Data Sonoma

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?

The description reveals detailed behavioral traits beyond annotations: data sources (SEC EDGAR/XBRL for companies, FAERS/FDA/clinicaltrials for drugs), handling of off-calendar fiscal years, result sorting by primary metric, and inclusion of citation URIs. Annotations already indicate readOnlyHint and idempotentHint, and the description aligns with them.

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 moderately concise but packed with valuable information. It front-loads the core purpose with example queries, then details data sources and behavior. Every sentence adds utility, though the initial quote list could be slightly streamlined 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?

For a tool with no output schema, the description thoroughly covers return values (paired data, URIs, sorted) and edge cases (off-calendar fiscal years). It explains the tool replaces 8-15 sequential lookups, providing a complete understanding of its value and behavior. Given the complexity of two entity types, the description leaves no obvious gaps.

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% with descriptive parameter fields. The description adds extra meaning by explaining what data each type retrieves and providing concrete examples (e.g., ['AAPL','MSFT'] for companies). This adds value beyond the schema definitions.

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 in a single call, providing specific verbs like 'compare' and citing example queries. It distinguishes itself from sibling tools like entity_profile by emphasizing parallel execution 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?

The description explicitly states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' offering clear when-to-use guidance. It does not explicitly mention when not to use, but the context implies it is for comparisons, not single entity lookups. The sibling list provides obvious alternatives like 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

A3.7/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded reuses the same router, and deep_research overlaps with ask_pipeworx for multi-part questions. Similarly, bet_research, polymarket_edges, polymarket_arbitrage, entity_profile, compare_entities, recent_changes, and resolve_entity all cluster around overlapping research/comparison tasks despite detailed descriptions.

Naming Consistency3/5

Names are consistently lowercase snake_case, but the naming pattern is mixed: some are verb_noun (ask_pipeworx, validate_claim, resolve_entity), some are bare nouns (datasets, metadata, polymarket_edges), some are imperative verbs (remember, forget, query), and some are adjective_noun (recent_alerts, recent_changes). The polymarket_* and pipeworx_* prefixes help, but the overall convention is not uniform.

Tool Count2/5

With 34 tools, the server exceeds the 25+ threshold and feels overstuffed for a coherent single-purpose MCP server. It spans unrelated domains: Sonoma County open data, a general structured-data router, prediction-market analysis, memory, subscriptions, npm dependency checking, and llms.txt generation—each could reasonably be its own smaller server.

Completeness4/5

The core research workflow is well covered: routing, grounded verification, entity resolution, entity profiles, comparisons, recent changes, claim validation, memory, subscriptions, and prediction-market execution checks are all present. Minor gaps exist, such as no subscription update/edit, no general pipeworx:// record-reader tool, and a read-only open-data surface, but agents can usually work around these.

Resources