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Newsdata

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?

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. Description adds details like handling off-calendar fiscal years, sorting by primary metric, and returning citation URIs, with no contradictions.

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 front-loaded with common query phrases and is informative, but slightly verbose. Could trim redundant parts while preserving all necessary details.

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 no output schema, the description adequately explains return format (paired data with citation URIs), sorting behavior, and the range of entities covered, making it complete for an agent.

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% with descriptions, and the description elaborates on what each type retrieves (e.g., company pulls revenue/net income/cash/debt; drug pulls FAERS/FDA/trial counts), adding significant meaning.

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 it performs side-by-side comparisons of 2–5 companies or drugs, specifying what data is pulled for each type. It distinguishes itself from siblings by advising preference 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 Guidelines5/5

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

Explicitly lists example queries and when to use ('ALWAYS PREFER over sequential single-pack lookups'). Provides clear context and alternatives.

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

A4/5.0
Disambiguation3/5

Most tools have clearly distinct roles, and the extensive descriptions help differentiate intent, but the ask_pipeworx family—especially ask_pipeworx_beta, which is currently identical to ask_pipeworx—creates real ambiguity. Overlapping entry points like ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim could also cause misselection without careful reading.

Naming Consistency4/5

All 34 tools use consistent snake_case, and clear verb-led or noun-prefixed patterns emerge across families like ask_pipeworx*, polymarket_*, and remember/recall/forget. Minor deviations such as ai_visibility_check and recent_changes being noun phrases rather than verb_noun constructions prevent a perfect score.

Tool Count2/5

34 tools is well above the 25-tool threshold for over-scoping, making the set heavy for an agent to navigate. While the server spans many domains, several tools like generate_llms_txt, scan_dependency, and ai_visibility_check feel tangential to the core news/research purpose and would be better split into separate servers.

Completeness4/5

The core news/research domain is well covered: lookup, grounded verification, deep multi-source research, entity profiles, comparisons, subscriptions, and alert feeds are all present with no obvious dead ends. Minor gaps exist—such as no direct full-text article retrieval or a dedicated free-text news search beyond latest_news filters—but agents can work around them.

Resources