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Unquant

Get a news summary

news_article
Read-onlyIdempotent

Return one processed news summary by story identifier. The tool does not return full article text or external links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
story_idYesThe story identifier from a news result.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes
billingYes
warningsYes

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety profile is covered. The description adds value beyond annotations by disclosing that the tool returns processed/summarized content and explicitly excludes full article text and external links — useful behavioral context the agent wouldn't get from annotations alone.

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?

Two tight sentences with zero waste. The first states the core action, the second adds the key exclusion constraint. Could arguably include sibling differentiation, but for what it contains, it's efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read-only tool with full schema coverage, a robust output schema, and strong annotations (readOnly, openWorld, idempotent), the description is largely complete. It adds the key boundary (summary-only, no full text/links). Minor gap: it doesn't hint at what fields the summary contains, though the output schema presumably covers that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the single parameter story_id has a regex pattern and description ('The story identifier from a news result'). The description references the story identifier but adds no new semantic detail beyond what the schema already documents, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states clearly 'Return one processed news summary by story identifier' — a specific verb (return) plus resource (news summary) with scoping by identifier. It also distinguishes itself by explicitly noting it does not return full article text or external links, though it doesn't name sibling alternatives like news_general or news_stock.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description implies usage by story identifier and indicates the tool is scoped to summaries versus full text, giving a sense of when it applies. However, it doesn't explicitly name alternatives like news_general or news_stock or provide when-not-to-use guidance. The 'from a news result' phrasing in the schema hints at upstream sourcing but that's not in the description itself.

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
Disambiguation5/5

Each tool targets a distinct resource-action combination (catalog items, datasets, macro data, market data, news, politics, account). Even within the market_ prefix, tools are clearly separated by resource type (quote, fundamentals, earnings, ratings, profile). No two tools appear to perform the same operation.

Naming Consistency4/5

The naming follows a consistent noun_verb pattern with domain prefixes: catalog_, datasets_, macro_, market_, news_, politics_. The verb style is consistent (describe, list, search, request, submit, return-type verbs like indicator and quote). Slight deviation with account_request_upgrade vs account_upgrade_status, and some verbs double as noun forms (quote, indicator, preview), but overall the convention is predictable.

Tool Count4/5

At 28 tools, the count is on the high side, but it serves a broad data platform spanning seven distinct domains (catalog, datasets, macro, market, news, politics, account). Each domain earns multiple tools to cover its surface, and the domains are broad enough to justify the volume. Slightly heavy, but reasonable given the scope.

Completeness4/5

The surface covers the full discovery-to-delivery workflow for data: list, describe, preview, request (catalog), plus direct dataset access. Market data has symbols search, quotes, price history, fundamentals, earnings, ratings, ETFs, and profile. Minor gaps include no bulk quote or multi-ticker endpoints, and there's no tool for reading an existing catalog request's status, but core workflows are well-covered.

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