Suggest Tag Improvements

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

No annotations are provided, so the description carries full burden. It transparently discloses the analysis steps (identify feature type, match preset, compare tags, suggest missing fields) and implies a read-only operation. It does not mention side effects, permissions, or rate limits, but the context (analysis tool) makes destructive behavior unlikely. Slightly more explicit read-only confirmation would elevate the score.

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 dense paragraph that efficiently conveys the tool's functionality. It is front-loaded with the core action. While concise, it could benefit from bullet points or clearer separation of steps for even quicker scanning, but it is not overly verbose.

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?

There is no output schema, so the description must explain return values. It mentions 'prioritized improvement suggestions with explanations and example values', but lacks specifics about the output structure (e.g., whether it returns an array of objects, fields like 'tag', 'reason', 'example'). Given the tool's complexity, more detailed return format expectations would improve completeness.

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 provides complete descriptions for both parameters (tags and options) with 100% coverage, so the description adds no additional parameter semantics. The baseline score of 3 is appropriate as the schema already explains parameter meaning and formats.

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 specific verbs ('analyze', 'provide suggestions', 'identifies', 'compares', 'suggests') and clearly defines the resource ('OpenStreetMap tag collection'). It distinguishes itself from siblings by describing a unique analysis workflow (finding matching OSM presets, comparing against requirements), which is not covered by other tools like validate_tag_collection or compare_tags.

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 explicitly states use cases: 'enhance incomplete features, learn best practices, or improve data quality'. This provides clear when-to-use guidance. However, it does not mention when NOT to use the tool or alternatives for specific scenarios, which would strengthen the dimension.

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