AxKnowledgeBase_search_private_paper_assets

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the operation is a ranked search, warns that the query must be Lucene syntax (not plain string), and mentions the result shape matches that of search_paper_assets. While it does not explicitly state that it is read-only or describe pagination, the description gives enough behavioral context for an agent to understand the tool's purpose and side-effect-free nature.

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 compact (three sentences) and front-loads the core purpose. It then adds the sibling relationship, a follow-up pointer, and a critical query-syntax warning. Every sentence earns its place, with no redundancy or filler.

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 search tool with four parameters, no output schema, and a clear sibling that defines the result shape, the description is reasonably complete. It explains the query syntax, the doc_id source, and the follow-up fetch tool. It does not describe the result fields, but it explicitly points to 'same result shape' as search_paper_assets, and the presence of a sibling with that detail makes the omission acceptable.

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 input schema covers 100% of parameters with descriptions, and the description itself adds little beyond what the schema already provides. The only added value is the explicit example of Lucene syntax and the note that doc_id comes from specific listing tools, but these are also present in the schema descriptions. Thus the description does not significantly enrich parameter understanding beyond the baseline.

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 opens with a specific verb ('Find'), a specific resource ('figures or tables in one paper of the organization's private knowledge graph'), and a clear criterion ('caption matches a query, ranked by relevance'). It explicitly names the sibling 'search_paper_assets' and distinguishes itself as its private counterpart, so an agent cannot confuse it with the public version or other knowledge base tools.

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 clearly positions this tool relative to its public sibling ('private counterpart of search_paper_assets') and states the difference ('different graph'). It also recommends the follow-up tool 'get_private_paper_asset' for fetching the result. However, it does not explicitly state when not to use it or provide alternative conditions (e.g., use this only for private papers, or use search_knowledge_base for a broader search), leaving some inference to the agent.

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