analyze_prompt

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

Annotations already indicate this is a read-only, non-destructive, idempotent operation with a closed-world scope, which the description does not contradict. The description adds minimal behavioral context by implying the tool evaluates prompt quality, but it does not elaborate on aspects like evaluation metrics, output format, or rate limits. Given the annotations cover key safety traits, the description's addition is limited but not contradictory, warranting a score above baseline.

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 disorganized list of keywords and translations (e.g., '프롬프트 분석|평가|점수|얼마나 좋은지|analyze prompt|rate this|score|how good|prompt quality') rather than a coherent sentence. It lacks structure and front-loading of key information, making it inefficient and cluttered without adding substantive value.

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 annotations provide clear safety hints (read-only, non-destructive) and the schema fully documents parameters, the description is minimally adequate for a simple analysis tool. However, it lacks details on output (no output schema) and does not explain what 'prompt quality' entails or how results are presented, leaving gaps in understanding the tool's full behavior and use cases.

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, clearly documenting both parameters ('prompt' and 'criteria'). The description does not add any meaningful semantics beyond the schema, such as examples of criteria or how the analysis is applied. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract from the schema's documentation.

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 is a tautology that essentially restates the tool name 'analyze_prompt' with synonyms and translations (e.g., '평가', '점수', 'rate this', 'score'), rather than clearly stating what the tool does. It mentions analyzing prompt quality but lacks specificity about what aspects of quality are evaluated or how the analysis is performed, failing to distinguish it from sibling tools like 'analyze_complexity' or 'suggest_improvements'.

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. It does not mention any context, prerequisites, or exclusions, nor does it reference sibling tools (e.g., 'enhance_prompt' for improvement suggestions or 'analyze_complexity' for complexity analysis). This leaves the agent with no information to make an informed choice among similar tools.

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