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Unicode

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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, etc. Description adds that results are sorted by primary metric for 'largest'/'biggest' queries, and correctly handles off-calendar fiscal years. 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?

Description is front-loaded with purpose, uses bullet-like lists, and every sentence adds value. Could be slightly shorter, but remains efficient and well-structured.

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 all aspects: intended usage, data sources (SEC EDGAR/XBRL, FAERS), sorting behavior, return format (paired data + citation URIs), and efficiency claim (replaces 8–15 lookups). No output schema, but description adequately explains returns.

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%, but description adds value by providing examples ('AAPL','MSFT'), explaining how type determines data sources, and clarifying value formats (tickers/CIKs for company, names for drug).

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 starts with common user phrasings and clearly states 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call'. It specifies the verb (compare), resource (entities), and distinguishes from siblings by advocating over sequential single-pack 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'. Provides example queries. While it doesn't list alternatives, the context of siblings (e.g., entity_profile) implies when not to use. Slightly lacks explicit when-to-avoid guidance.

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
Disambiguation3/5

Several tools overlap significantly: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded serve nearly the same routing purpose, with the beta variant currently identical to the stable one, and deep_research also overlaps for broad research. However, most other tools have clearly distinct functions, and descriptions provide usage guidance, so ambiguity is moderate.

Naming Consistency3/5

Most names are snake_case and readable, but patterns vary between verb_noun (compare_entities, resolve_entity), noun phrases (entity_profile, polymarket_edges), and bare verbs (remember, subscribe). The pipeworx_ and polymarket_ prefixes are used inconsistently across the set, and the server name 'Unicode' does not align with the tool names.

Tool Count2/5

At 34 tools, the server is overloaded for a focused purpose, especially since only three tools relate to Unicode despite the server name. Many Polymarket and Pipeworx tools could be consolidated, and the count exceeds the well-scoped range of 3-15 tools, making the set feel bloated and unfocused.

Completeness2/5

The server name claims to be about Unicode, but only char_info, escape_string, and unescape_string cover that domain, missing common operations like normalization, case conversion, and encoding validation. For the broader data-access domain the surface is fairly complete, yet there is no tool to fetch a specific pipeworx:// citation URI, leaving cited records unfetchable within the tool set—an obvious gap relative to the stated capabilities.

Resources