add_knowledge

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

No annotations are provided, so the description carries full burden for behavioral transparency. The description only states the basic action without disclosing important behavioral traits such as whether adding knowledge is append-only, if duplicates are handled, if there are limits on number of items or content length, or any authentication requirements. This leaves significant gaps for the agent to infer behavior.

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 concise with just two sentences. The first sentence states the main action and object, and the second sentence provides examples of use. Every sentence adds value without redundancy, making it easy for an agent to quickly grasp the tool's function.

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?

Given the tool's moderate complexity (5 parameters, 3 required, no output schema), the description covers the basic use case but lacks completeness. It does not explain the effect of adding knowledge (e.g., whether it overwrites or appends), the maximum length of content, or any constraints. More context would be needed for a fully self-contained definition.

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 100%, so the baseline is 3. The description adds some context by mentioning examples of knowledge content but does not provide additional semantics beyond what the input schema already specifies for each parameter. It adds marginal value.

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 purpose: 'Add a knowledge base item to an existing AI sales agent.' It lists specific types of information (product info, FAQs, policies), making the action concrete. The tool is well-distinguished from siblings (create_sales_agent and generate_qr_code), which have entirely different functions.

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 provides clear usage guidance: 'Use this to provide product info, FAQs, policies, or other information the agent should know.' It directly tells the agent when to invoke the tool. However, it does not explicitly mention when not to use it or suggest alternatives among siblings, which would slightly improve the score.

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