Analysiere Lesbarkeit

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

With no annotations, the description must convey behavior. Saying 'Berechnet' (calculates) implies a read-only analysis, and the mention of specific metrics adds some transparency. However, it does not explicitly state that no modifications occur, nor does it describe the output structure or any potential side effects.

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, front-loaded sentence that efficiently communicates the core function. Every word contributes; there is no redundancy or irrelevant detail.

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?

With no output schema, the description should provide some indication of the return format or result structure. It mentions metrics but not whether they are returned as a score, a breakdown, or a single value. The lack of guidance on applicable post types or prerequisites makes it incomplete for an agent to fully anticipate the tool's behavior.

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 fully documents the only parameter (postId) as 'Post/Page ID' (100% coverage). The description adds no additional parameter meaning beyond that, so the baseline score of 3 is appropriate.

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 uses a specific verb 'Berechnet' (calculates) and clearly identifies the resource as readability metrics, naming concrete examples (Flesch, average sentence length). It distinguishes itself from sibling analysis tools by focusing on readability.

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 guidance is provided on when to use this tool versus readability-related alternatives like seo_analyze_content or perf_analyze_content. The description simply states what it does without any contextual use cases or exclusions.

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