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

With no annotations provided, the description carries the full disclosure burden. It clarifies the dual return (credit cost + current balance) and identifies the return format as 'a text summary.' However, it omits operational traits: whether the call consumes credits (likely not), idempotency guarantees, rate limits, or permission requirements. Basic behavioral context is present but safety/operational details are sparse.

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 follows a clear docstring structure (summary, Args, Returns) with the main purpose front-loaded in the first sentence. While the Args section duplicates information already present in the 100%-covered schema, the formatting is efficient and every sentence earns its place by clarifying inputs or outputs. Length is appropriate for a three-parameter tool.

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?

Given high schema coverage (100%), clearly defined enums in the schema (mapping to sibling operations), and existence of an output schema, the description is sufficiently complete. It adds necessary domain context ('maskr.io') and clarifies the return type. It appropriately does not replicate detailed return value documentation since an output schema exists.

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?

Input schema has 100% description coverage, establishing a baseline of 3. The Args section in the description lists the three parameters but essentially mirrors the schema content without adding syntactic nuances (e.g., it repeats 'The service to check pricing for' from the schema and omits the schema's crucial upscaling dimension note: 'provide the INPUT dimensions'). Since schema coverage is complete, the description serves as readable documentation but adds minimal semantic value beyond structured data.

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 opens with 'Check how many credits a maskr.io service costs' — a specific verb (check) + resource (credit cost) + domain context (maskr.io). It clearly distinguishes from siblings: unlike 'remove_background' or 'upscale' (which perform processing), this queries pricing; unlike 'get_account_balance' (which only returns balance), this calculates service-specific costs based on dimensions.

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 implies usage context by mentioning 'image dimensions' and 'service,' hinting it precedes processing calls. However, it lacks explicit guidance such as 'use this before calling remove_background/upscale' or 'use get_account_balance if you only need your balance without cost calculation.' No when-not-to-use or alternative specifications are provided.

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