List offers
list_offers按目标 / 地区 / 模型标签筛选免费 AI 额度列表。List free AI credit offers filtered by goal, region, or model tag.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | ||
| limit | No | ||
| locale | No | ||
| region | No | ||
| model_tag | No |
list_offers按目标 / 地区 / 模型标签筛选免费 AI 额度列表。List free AI credit offers filtered by goal, region, or model tag.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | ||
| limit | No | ||
| locale | No | ||
| region | No | ||
| model_tag | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only that the offers are 'free AI credit' listings; it says nothing about pagination or result size despite a `limit` parameter. With annotations carrying the heavy load, a 3 is appropriate.
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 text is short and front-loaded, but it is a bilingual duplicate that says exactly the same thing in Chinese and English, which is wasted space for a single-language agent. It is not bloated, but it is not maximally efficient either.
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?
With 5 parameters, 0% schema description coverage, and no output schema, the description should explain at least the pagination/size behavior of `limit` and the purpose of `locale`. Neither appears, leaving real gaps for an agent that wants to page through or localize results.
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%, so the description must compensate, and it names three of five parameters (goal, region, model_tag) while omitting `limit` and `locale` entirely. The enum values live in the schema, so the description adds only marginal value over the structured fields.
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?
States a specific verb (list/filter) and resource (free AI credit offers) plus the filter dimensions, so the agent can tell it is a filtered listing tool. It does not distinguish itself from siblings like search_offers or get_offer, which is the only thing missing from a 5.
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 names filter dimensions but gives no when-to-use guidance, no exclusions, and never mentions the sibling tools search_offers or get_offer. An agent cannot tell from this text when to browse with list_offers versus searching with search_offers.
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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