rag_search_knowledge

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only search and loosely notes the return shape ('list: Matching knowledge entries'), but says nothing about result limits, ranking, pagination, or required permissions. For a search over a knowledge base with zero annotation coverage, this is thin.

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?

Short and front-loaded: purpose first, then a compact Args/Returns block with no filler. The docstring-style formatting is slightly robotic but every line carries information.

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-parameter, no-output-schema read tool, the description covers the essentials an agent needs to invoke it. It falls short only on the sibling disambiguation and return-detail front, neither of which is fatal at this complexity level.

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 single parameter has no schema-level description at all, so the description must compensate. It does add value by giving concrete example queries ('价值投资', '周期'), clarifying that this is a semantic/free-text lookup rather than an ID lookup, but it does not specify language handling or query length constraints.

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 clear verb+resource ('Search the investment knowledge base'), which is better than a tautology. However, it does not distinguish this tool from several close siblings such as rag_rag_search_reports, rag_ask_investment, or user_knowledge_search, so an agent cannot tell which search surface to pick without opening schemas.

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?

No when-to-use guidance is given and no alternative is named. With siblings like rag_ask_investment (question answering) and user_knowledge_search (user-specific knowledge) present, the absence of routing guidance leaves the agent to guess.

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