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List states for a country

list_states
Read-onlyIdempotent

List the state codes available for state-level geo-targeting in a country (used as the "state" parameter on the scrape tools). Only countries with state-level targeting are accepted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryYesISO 3166-1 alpha-2 country code to list states for. Only countries with state-level targeting are supported.

TDQS

A4/5.0
Behavior3/5

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

Annotations already cover the safety profile: readOnlyHint, idempotent, and non-destructive. The description adds that only state-targeting countries are accepted and that output plugs into scrape tools, but it does not describe result format, pagination, or other behavioral details. Given the annotations, this is acceptable but not outstanding.

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?

Two sentences, front-loaded with the core action and resource, and a second sentence for the limitation. No redundant or filler text.

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 simple single-parameter listing tool, the description covers purpose, the main constraint, and the connection to sibling scrape tools. It does not spell out the exact return shape, but the phrase 'List the state codes' sufficiently implies an array of code values. The absence of an output schema makes this a minor gap only.

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?

Input schema coverage is 100% and the only parameter, country, already has a clear description and enum. The tool description adds context about how the result is used, but it does not add new parameter-level semantics beyond the schema. Baseline 3 applies because the schema carries the load.

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 clearly states a specific action and resource: listing state codes for country-level geo-targeting, and explicitly connects to the 'state' parameter used by scrape tools. It distinguishes itself from siblings like list_countries and scrape_* tools by specifying exactly what it returns and why.

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 implies when to use this tool: when you need valid state codes for a country before calling a scrape tool. It also states a constraint (only countries with state-level targeting are accepted). It does not explicitly name alternatives or exclude cases, but the context is clear enough.

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
Disambiguation5/5

Each tool targets a distinct engine or product (ChatGPT, Copilot, Gemini, Google, Google News, etc.), and the descriptions clearly specify what each scrape returns. The only potential overlap is between Google search and Google AI Mode, but the descriptions separate them effectively.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern: list_* for metadata and scrape_* for retrieval operations. The engine-specific names like scrape_chatgpt and scrape_google_ai_mode are predictable and easy to group.

Tool Count5/5

Ten tools is a well-scoped size for a geo-targeted search and AI answer scraping server. Each tool covers a meaningful engine or metadata requirement without excessive redundancy.

Completeness4/5

The tool surface covers major AI assistants, Google search variants, news, and supporting geo-targeting metadata. Minor gaps exist such as no standalone Bing/DuckDuckGo scraper or explicit engine model listing, but the core workflows are well supported.

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