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Duffel

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

A4.8/5.0
Behavior5/5

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

Adds significant behavioral detail beyond annotations: handles off-calendar fiscal years correctly, sorts results by primary metric, returns paired data with citation URIs. No contradiction with annotations (readOnlyHint, openWorldHint, idempotentHint).

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?

Single paragraph with no wasted words. Front-loaded with common user queries. Each sentence adds unique value (purpose, usage preference, parameter details, behavioral notes). Perfectly sized for its complexity.

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?

Given the tool's complexity (dual entity types, different data sources, sorting, citation URIs), the description covers all essential aspects. No output schema, but description adequately explains return format ('paired data + citation URIs'). Complete and self-sufficient.

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?

Both parameters (type and values) are described in detail beyond schema: explains what each type pulls (revenue, net income for company; adverse events, FDA approvals for drug). Schema coverage is 100%, and description adds rich semantics for each field.

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 uses specific verbs like 'compare', 'side-by-side comparison', and concrete phrases ('which is bigger / better'). Clearly distinguishes from sibling tools by stating it replaces 8–15 sequential lookups, which differentiates it from single-entity tools like entity_profile.

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 states to 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing a clear when-to-use directive. While not mentioning when not to use, the context is well-defined. Minor room to mention alternatives for non-comparison tasks.

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

The set is organized into clusters (Pipeworx querying, Polymarket analysis, entity research, subscriptions, memory), but several tools within a cluster have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, deep_research, and validate_claim all answer questions, and polymarket_edges, bet_research, and polymarket_arbitrage all surface trading opportunities. The very detailed descriptions help an agent choose correctly, but the boundaries are not crisp enough for a 4.

Naming Consistency3/5

Most names are lowercase snake_case and there are consistent prefixes like polymarket_ and pipeworx_, which aids predictability. However, the verb/noun ordering is inconsistent across the set (ask_pipeworx, bet_research, entity_profile, duffel_flight_search, ai_visibility_check), and some names are noun-heavy while others are verb-first. It is readable but not a uniform convention.

Tool Count2/5

At 32 tools the surface feels heavy for a coherent server; the rubric treats 25+ as too many. Several tools are wrappers or variants of the same underlying capability (ask_pipeworx_beta, polymarket_edges vs bet_research, ai_visibility_check vs scan_competitor_ai_presence), so the count overstates real functional breadth.

Completeness3/5

The research/data side is very complete: querying, grounded verification, deep research, entity resolution, comparison, profiles, monitoring, memory, and feedback are all covered. However, the Duffel flight tool only searches and never books, so if the server is meant to be a flight agent there is a notable dead end; the broader toolkit also lacks direct CRUD for most resources beyond subscriptions.

Resources