Read a category-level overview essay. Topics: anatomy (what a fiber laser machine is made of), laser-sources, cutting-heads, welding-heads, control-systems, cladding-cleaning. Written in Chinese; translate for the user as needed.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly uses 'Read' to indicate a non-destructive operation and discloses that the content is in Chinese with translation needed. It lacks details on return format or error behavior, but for a simple read tool this is reasonably transparent.
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 three concise sentences: purpose, topic list, and language note. Every sentence adds value, and the main action 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?
This is a simple read tool with one parameter and no output schema. The description covers purpose, topics, and translation behavior. It could specify the exact return format, but 'essay' implies text, and the description is mostly complete for the tool's complexity.
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 0%, and the description compensates by enumerating concrete topic values (anatomy, laser-sources, cutting-heads, etc.). This gives clear guidance for the 'topic' parameter, adding meaning far beyond the bare schema.
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's function: 'Read a category-level overview essay.' It specifies the verb and resource, and the list of topics (anatomy, laser-sources, etc.) distinguishes it from sibling tools like get_part_card or search_parts_knowledge.
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 when to use the tool (for reading overviews on the listed topics) but does not explicitly state alternatives or when not to use it. The note about translation provides a usage hint, but there is no exclusionary guidance or reference to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: search for cards, fetch full card, get overview, list brands, and submit inquiry. No overlap or ambiguity between them.
All tool names follow a clear verb_noun pattern with underscores (get_brand_overview, get_part_card, list_brands, search_parts_knowledge, submit_inquiry). Consistent and predictable.
5 tools is well-scoped for a knowledge base server. It covers browsing, searching, retrieving details, and contacting support without being too sparse or bloated.
The tool surface fully supports the intended domain: overview, search, full card retrieval, brand listing, and human inquiry. No obvious missing functionality for this knowledge base use case.