Convert Flat Text to JSON

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

With no annotations, the description must carry behavioral disclosure. It explains handling of whitespace, empty lines, comments, and output format. Does not detail error handling or limitations, but covers essential behaviors.

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?

Sentences are generally concise and front-loaded with the main action. Minor redundancy in mentioning AI workflows and essential processing, but overall efficient.

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 simple one-parameter converter without output schema, the description adequately covers input variants, use cases, and output nature. Could mention return type explicitly, but sufficient.

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?

Schema description coverage is 100%, so baseline is 3. The description reinforces input format details already in schema, adding context like ignoring comments and trimming whitespace, but no significant new meaning.

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 converts flat text (key=value per line) to JSON object format. It specifies the exact input format and output, distinguishing it from siblings like json_to_flat.

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?

Explicitly advises using it FIRST when receiving flat text tags, positioning it as an input converter. Mentions specific sources like OSM exports. Lacks explicit when-not-to-use or alternatives, but context suffices.

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