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

With no annotations, the description carries the full burden of behavioral disclosure. It adds meaningful details: the call body shape ({input} -> {ok, value, warnings}), the limitation to a YAML subset, the lack of runtime dependency, and the per-call cost on Base. This goes well beyond a bare verb phrase, though it doesn't cover how invalid input is handled beyond warnings.

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?

Two tight sentences, each earning its place. The core conversion action and scope are front-loaded, followed by the output envelope and cost. No filler or redundancy.

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 one-parameter tool with an output schema present, the description covers the essential operational details: input format, supported YAML subset, output shape with warnings, and cost. Nothing critical is missing for an agent to invoke it correctly.

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% because the single 'input' parameter is already documented as 'YAML document text'. The description reinforces the body shape and YAML scope but adds little new semantics beyond what the schema provides. Baseline 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 ('Converts') with a clear resource ('YAML subset ... into JSON'), and even enumerates the supported YAML features (block maps, sequences, nested indentation, scalars, comments). This makes the tool's purpose immediately understandable and distinct from its siblings such as repair_json or text_extract.

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 clearly indicates when this tool is appropriate: when a YAML document needs to be converted to JSON. It doesn't explicitly discuss alternatives or exclusions, but the context is clear enough that an agent can infer the primary use case without ambiguity.

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