mcai_listLists all knowledge-base terms, optionally filtered by category, so users can review coverage or choose a concept from the catalog. Returns term names and classifications only, not full definitions.
列出知识库中的全部术语（可按体系过滤），用于了解覆盖范围、或让用户从目录中选择。当用户问“这套学说有哪些概念”“你们收录了什么”时使用。分工：按关键词找词用 mcai_search；要某条完整词条用 mcai_concept。边界：只返回术语名与分类，不返回定义全文。
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | 按体系过滤，取值必须是：元意识体系 / 本体论模型 / 序生体系 / 元子社会；留空则返回全部 |
Changes observed during successful MCP inspections.
v0.1.2Input schema / properties / category / descriptionPrevious value: -"按体系过滤：元意识体系 / 本体论模型 / 序生体系 / 元子社会；留空则返回全部"New value: +"按体系过滤，取值必须是：元意识体系 / 本体论模型 / 序生体系 / 元子社会；留空则返回全部"v0.1.1Input schema / additionalPropertiesAdded value: +falseInput schema / properties / category / descriptionAdded value: +"按体系过滤：元意识体系 / 本体论模型 / 序生体系 / 元子社会；留空则返回全部"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds genuinely new behavioral detail — that only term names and categories are returned, not full definitions — which prevents misuse. It does not mention pagination or result-size behavior for a potentially large list, keeping it below a 5.
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?
Front-loads the core action and filter, then usage triggers, then sibling division, then output boundary — each clause is load-bearing with no filler. Length is justified by the routing value it provides among four siblings.
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?
For a one-optional-param read tool with full annotation coverage and no output schema, the description still specifies the return shape (names + categories) and its scope limitations. Nothing an agent needs to call it correctly or to avoid confusing it with siblings is missing.
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 coverage is 100% and the schema itself enumerates the four allowed category values plus the empty-means-all behavior. The description only repeats "可按体系过滤" without adding syntax or format guidance, so the baseline 3 applies.
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?
Names a specific verb and resource ("列出知识库中的全部术语") plus an optional filter, and explicitly delineates itself from mcai_search and mcai_concept. An agent can tell exactly which sibling to pick without opening any schema.
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?
Gives concrete user phrasings that should trigger it ("这套学说有哪些概念"、"你们收录了什么") and an explicit division of labor with the two sibling tools. It also states the boundary that definitions are not returned, which further routes the agent to mcai_concept when full entries are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.