CanYouGrab.it

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

Despite annotations declaring readOnly/openWorld/idempotent status, the description adds valuable behavioral context about the return data: 'confidence, source, cache age, and ambiguous results.' This discloses data quality characteristics (caching, uncertainty handling) and partial failure modes that annotations don't capture, which is crucial for an openWorld lookup tool.

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 sentences with zero waste. The first front-loads the purpose and trigger condition; the second explains return characteristics. Every clause earns its place—no redundancies with the title or schema structure.

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 the tool's simplicity (single array parameter) and rich annotations covering safety profiles, the description satisfactorily covers the behavioral gaps by explaining return value semantics (confidence levels, cache age) in lieu of an output schema. Only minor gap is lack of parameter format specifics.

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?

With 0% schema description coverage, the description minimally compensates by stating 'one or more domains,' which confirms the array cardinality. However, it lacks format specifications (e.g., whether to include TLDs, 'www' prefixes, or IDN support) that would fully compensate for the undocumented schema parameter.

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 checks 'whether one or more domains are available to register,' providing a specific verb ('check') and resource ('domains'). The phrase 'available to register' effectively distinguishes this from the sibling 'check_usage' tool, clarifying this is about registration availability rather than usage statistics or traffic.

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 opens with 'Use this when...' providing explicit guidance on the trigger condition (user wants availability information). While it doesn't explicitly name 'check_usage' as an alternative, the specific focus on 'available to register' provides clear contextual boundaries for when this tool is appropriate versus its sibling.

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 establish safety (readOnly, non-destructive, idempotent); description adds valuable context about the data scope (current billing period) and content (plan, usage, quota) that annotations don't cover. No contradictions with annotations.

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?

Single sentence that front-loads the usage condition and packs specific resource details. No redundancy or waste—every clause earns its place.

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 zero-parameter read-only tool, description adequately covers the semantic content of the return value (plan, usage, quota) despite missing output schema. Full completeness would benefit from output schema details, but description sufficiently enables invocation decisions.

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 0 parameters, which per rubric establishes a baseline of 4. Description appropriately focuses on tool behavior rather than parameters.

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?

Description clearly defines the action (retrieve/see) and specific resources (plan, usage, remaining quota) with scope (current billing period). It implicitly distinguishes from sibling 'check_domains' by specifying these billing-related resources.

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 states the trigger condition ('when the user wants to see...'), providing clear guidance on when to invoke. Lacks explicit mention of when NOT to use or direct sibling comparison, but the condition is specific enough to differentiate from domain checking.

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