claude_generate

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions 'retry and model selection' as features, it doesn't describe what 'Generate code or text' actually entails - whether this is a one-shot generation, conversational interaction, or something else. It doesn't mention authentication requirements, rate limits, cost implications, or what happens when the tool fails. For a complex tool with 14 parameters, this is a significant transparency gap.

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 a single, efficient sentence that gets straight to the point. It mentions the core action, the mechanism, and two key features. There's no wasted verbiage or unnecessary elaboration. However, it could be slightly more front-loaded by stating the primary purpose more prominently before mentioning implementation details.

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 tool with 14 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, how errors are handled, or the nature of the generation process. The agent must rely entirely on the parameter names and schema descriptions to understand this tool's behavior, which is insufficient for a generation tool that likely produces variable outputs and has significant configuration options.

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 100% schema description coverage, the input schema already documents all 14 parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions 'retry' (which maps to maxRetries) and 'model selection' (which maps to model), but doesn't provide additional context about parameter interactions or best practices. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 action ('Generate code or text') and the mechanism ('via Claude Code CLI'), which is specific and actionable. However, it doesn't explicitly differentiate this tool from its siblings (claude_edit, claude_edit_json, claude_generate_json, claude_refactor), which all appear to be Claude-related generation/editing tools. The description mentions 'retry and model selection' which are implementation details rather than core purpose differentiation.

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 no guidance on when to use this tool versus its siblings. There's no mention of when this generation tool should be chosen over claude_generate_json or claude_edit, nor any context about appropriate use cases. The agent must infer usage from tool names alone, which is insufficient for optimal tool selection.

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