Boost Prompt

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

Annotations indicate readOnlyHint=true (safe operation), openWorldHint=true (handles diverse inputs), and idempotentHint=false (non-idempotent). The description adds value by specifying the transformation is for 'clarity and effectiveness' and involves 'prompt engineering best practices', which provides behavioral context beyond annotations. However, it doesn't detail aspects like rate limits, error handling, or output format, keeping the score moderate.

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 front-loads the core action ('Transform a prompt') and adds necessary context without waste. Every word contributes to understanding the tool's purpose, making it appropriately sized and well-structured.

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 tool's moderate complexity (transformation operation), annotations cover safety and input handling, but there's no output schema to explain return values. The description adequately states the purpose but lacks details on usage guidelines, behavioral nuances like transformation specifics, or how it differs from siblings, leaving gaps in completeness for an AI agent.

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 input schema has 100% description coverage, with the 'prompt' parameter well-documented as 'Prompt to transform and optimize'. The description adds marginal meaning by implying optimization for 'clarity and effectiveness', but it doesn't provide additional syntax, examples, or constraints beyond the schema. Baseline 3 is appropriate given high schema coverage.

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 tool's purpose with a specific verb ('Transform') and resource ('prompt'), and it adds context about 'prompt engineering best practices' and goals like 'maximum clarity and effectiveness'. However, it doesn't explicitly differentiate from sibling tools like 'crafting_prompt' or 'fix_prompt', which might have overlapping or distinct functions, preventing a perfect score.

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 alternatives such as 'crafting_prompt' or 'fix_prompt'. It implies usage for optimizing prompts but lacks explicit when/when-not scenarios, prerequisites, or comparisons to siblings, leaving the agent with minimal context for selection.

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