China Bank Offers Facts

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

Annotations already cover safety (read-only, idempotent, non-destructive). The description adds behavioral context: 'Paid source-first' suggests source prioritization, and 'Returns every matching official document with complete cleaned text, source URL, hash and activity status' discloses the return payload details. This goes beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The first sentence states scope and source priority; the second details the return contents. Every word earns its place, and key information is front-loaded.

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

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

The description provides return fields and a full-result guarantee, but omits parameter details, output schema (none exists), and any usage context such as pagination or prerequisites. For a simple 2-parameter read tool with strong annotations, it is adequate but has notable gaps in parameter semantics and usage guidance.

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

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

Schema description coverage is 0%. The description does not mention either parameter (bank_code or activity_status) or their meanings. It only hints at 'one supported bank' but fails to explain how to specify it or what activity_status controls. There is no compensation for the low schema coverage.

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

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

The description clearly identifies the tool's action ('query') and resource ('official bank offer documents'). It distinguishes from sibling tool 'list_supported_banks' by specifying it operates on a single supported bank. The mention of returning 'every matching official document' adds precision.

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

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

The description gives no explicit guidance on when to use this tool versus alternatives like list_supported_banks. It implies a prerequisite (a specific bank) but does not state scenarios or exclusions. No when-not-to-use or alternative references are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare the tool safe (read-only, idempotent, non-destructive). The description adds value by stating this is a 'free' capability check and listing specific outputs (data freshness, coverage state, enabled status), which are useful behavioral details beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the key point ('Free capability check') and then enumerates the exact outputs. No wasted words.

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

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

Given the tool's low complexity (no params, simple list) and rich annotations, the description fully covers what the tool returns and its purpose. It is complete for an agent to understand when to invoke it.

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

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

The tool has zero parameters, so the description does not need to explain any. Per the rubric, zero parameters gives a baseline of 4, and the description adds sufficient context about the tool's outputs to justify this score.

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

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

The description clearly states the tool lists banks, data freshness, coverage state, and the enablement status of a sibling tool. The verb 'lists' is specific, the resource is banks plus relevant metadata, and the scope distinguishes it from get_bank_offers.

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

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

The description implies a use case: performing a free capability check before using get_bank_offers, especially by indicating whether that tool is enabled. However, it does not explicitly say 'use this before get_bank_offers' or provide exclusions, so it falls short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.