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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds that results can reveal failed or stale sources, which hints at the lifecycle states returned. However, since an output schema exists, the enumerated return fields largely duplicate structured data rather than adding new behavioral context, so this sits at the baseline.

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?

Two dense sentences, front-loaded with the resource and its returned fields, then the usage guidance and the sibling routing. Nearly every clause earns its place, though the field enumeration partially restates the output schema and could be trimmed.

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 zero-required-parameter list tool with full annotation coverage, a rich output schema, and 100% schema coverage, the description supplies enough routing and intent context to invoke it correctly. The only minor gap is that it does not mention the filter parameters an agent could combine with it, though the schema covers those adequately.

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 limit, cursor, status, and source_type are each documented in the schema with ranges, defaults, and examples. The description mentions 'type' and 'status' only as returned fields, not as filterable parameters, and adds no syntax or semantic detail beyond the schema. 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 ('List the knowledge sources'), immediately scopes it to the workspace's SuperBot agent, and enumerates the returned fields (type, status, entry count, last sync time, trained Q&A count). It also explicitly distinguishes itself from search_knowledge, so an agent can route correctly 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?

Gives three concrete use cases ('audit what the AI knows', 'spot failed or stale sources', 'what have we taught the bot') and names the alternative tool with the condition that selects it ('To search inside the content, use search_knowledge'). This is explicit when-to-use plus when-not-to-use.

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