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

No annotations exist, so the description carries the full burden. It discloses the use of Claude AI and that the output is accessible text with highlights and a recommended next action, which is useful. However, it doesn't mention cache behavior, latency/cost, or potential variability of AI-generated content despite the forceRefresh parameter.

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 two sentences, front-loaded with verb and resource, and contains no redundant filler. Every phrase adds information: narrative, client, AI, and output structure.

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?

The description explains the return type in words, which matters because no output schema exists. Yet it omits when to use, cache behavior, and service dependencies; for an AI generation tool with no annotations, this is adequate but not complete.

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?

The schema covers all three parameters with descriptions, so baseline is 3. The description doesn't add parameter-level detail, but the schema already documents each field adequately, so no compensation is needed.

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 starts with 'Gera narrativa personalizada...' providing a specific verb and resource. It clearly distinguishes this from sibling tools by focusing on AI-generated textual insights for a client, not on dashboards or list operations.

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?

There is no explicit when-to-use or alternative/exclusion guidance. The description implies the tool is for generating client-specific narratives but never tells the agent when to prefer it over similar report/insight tools like dashboard_executivo or saude_financeira.

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