Leafmelt

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

Annotations already establish readOnly, idempotent, openWorld and non-destructive behavior, and the description usefully adds the 1-5 document batch cap, the no-OCR limitation, and the returned fields (markdown, format, characters, approxTokens, truncated). It does not disclose rate limits, auth needs, or per-document failure behavior, so it stops short of a 5.

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?

Three dense sentences with zero filler: purpose and formats first, then input mechanics, then return shape and the exclusion. The most decision-relevant information is front-loaded.

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 correctly names the return fields, and it covers formats, batch size, input modes, and the OCR limitation. The main remaining gap is maxChars and truncation semantics, which are hinted at only via the returned 'truncated' field.

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 coverage is only 33% and maxChars has no description in either schema or description, so its meaning and default are left unexplained. The description does add real value by clarifying that urls and files are alternative input channels and by describing the base64 file shape, which partly compensates for the coverage gap.

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?

States a specific verb (Convert) plus resource (documents) with an explicit enumeration of supported formats, batch bounds (1-5), and the output target (clean Markdown for reading or RAG). An agent can distinguish this from the sibling supported_formats, which merely lists formats rather than performing conversion.

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 routes between the two input modes ('Pass public URLs in urls, or files as [{name, base64}]') and gives a clear exclusion ('Not for images or scanned PDFs (no OCR)'). It does not name the sibling supported_formats as the place to check format support, so it falls just short of full alternative-routing.

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

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

Annotations already declare the full safety profile (readOnly, idempotent, non-destructive, openWorld), so the description's burden is lower. It adds value by disclosing the shape of the payload (formats with extensions and MIME types) in the absence of an output schema, but says nothing about caching, scoping, or whether the list is stable.

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?

A single front-loaded sentence with zero filler. The verb and resource come first, and the return contents are appended as a compact qualifier.

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 must carry the return-value burden, and it does describe the three fields returned. For a zero-parameter static listing tool this is close to complete; only the absence of any note about freshness or relationship to convert_to_markdown is missing.

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 tool takes no parameters, so per the rubric the baseline is 4. The description correctly implies there is nothing to pass because the result is a static enumeration of supported 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?

States a specific verb and resource ("List the document formats Leafmelt converts") and adds what each entry contains (extensions, MIME types). It is plainly distinguishable from the only sibling convert_to_markdown, though it never names or contrasts with that sibling explicitly, which keeps it short of a 5.

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 explicit when-to-use statement, no exclusions, and no mention of the alternative convert_to_markdown. Usage is only implied: an agent can infer this is the discovery call to make before attempting a conversion, which matches the 'implied usage' bar of 3.

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