Ultrabrain Update

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

The description mentions 'update' which aligns with the destructiveHint annotation. However, it does not elaborate on side effects, permissions, or whether updates are reversible. The annotation already indicates destructiveness, so the description adds minimal behavioral context beyond the annotation.

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?

One sentence efficiently communicates the core action. However, it could be slightly more structured (e.g., listing key fields) without adding length.

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 high parameter count and presence of nested objects, the description is too brief. It does not mention required thought_number, optional session_id, or response_format, leaving agents without sufficient context 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?

Schema coverage is low (21%) and the description only mentions a subset of parameters (evidence, confidence, risks, actions, quality metrics). It does not explain format, constraints, or purpose of omitted parameters like tags, assumptions, or alternatives. The quality_metrics object is described in schema but not in the description.

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 indicates the tool updates an existing thought, listing specific fields like evidence, confidence, risks, actions, or quality metrics. This distinguishes it from sibling tools like ultrabrain_think (for generating thoughts) and ultrabrain_validate (for validation).

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 explicit guidance on when to use this tool vs alternatives. It does not specify prerequisites (e.g., thought must exist) or when to prefer ultrabrain_update over ultrabrain_validate or ultrabrain_analyze.

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