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

Annotations already declare readOnlyHint=false, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavior the annotations don't: 'thorough' runs three passes at ~3x credit, the call runs against the workspace's inference credit (a real cost signal), and it may return 'needs_confirmation'. That is meaningful extra context, though latency/citation-failure behavior is unaddressed.

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?

Purpose is front-loaded, then cost/behavior details follow. The prose is dense but each sentence carries information (depth, focus, credits, confirmation). Slightly long but no clear 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 complex, credit-consuming, web-touching tool with no output schema, the description covers the essential stakes: what is produced, where it is stored, cost, and the needs_confirmation return. It stops short of explaining the required id parameters or the approval flow, but is largely complete for correct invocation.

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?

With only 33% schema coverage the description must compensate, and it does explain the two most important optional params: what 'depth: thorough' entails and what 'focus' steers. However, required params fieldId and nodeId and the approvalId parameter receive no explanation, so the required inputs remain opaque.

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 specific verb and resource: 'Web-sourced secondary research on a node's idea — market context with citations, stored on the node.' This clearly conveys what the tool produces and where it lands. It does not, however, name or differentiate itself from plausible siblings like prism_nodes_expand or prism_research_digest, so an agent still has to infer which research path to pick.

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 solid conditional guidance for parameter selection: pass 'focus' whenever the user has said what they want to know, otherwise a generic brief is answered, and use 'thorough' for broader coverage. But it offers no when-to-use/when-not guidance relative to sibling tools such as prism_nodes_expand, leaving tool selection to inference.

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