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

No annotations provided, so description carries full burden. It adds valuable domain context explaining what credits are used for (1 per CV/cover letter order), but lacks operational details like error handling, what happens if phone number not found, or caching behavior.

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?

Perfectly concise with two sentences. First states purpose immediately; second provides essential domain context about credit costs. Zero 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 simple single-parameter read operation without output schema, the description is nearly complete. It explains the credit system which is essential domain context. Minor gap: doesn't hint at return value structure or error states.

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 has 100% coverage with phoneNumber fully documented. Description mentions 'customer' which loosely maps to the parameter, but adds no additional semantics, format constraints, or examples beyond what the schema already 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?

Excellent clarity: specifies the verb 'Check', resource 'credits', and scope 'remaining'. The second sentence distinguishes the domain context (CV/cover letter tailoring) which differentiates this from generic balance checking tools.

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?

Provides implied usage context by explaining that orders cost 1 credit, suggesting this should be checked before placing orders. However, lacks explicit when-to-use guidance or direct comparison to siblings (get_pricing, place_order).

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully explains the business logic (career phases) and workflow ordering (must precede place_order), but lacks technical behavioral traits such as whether the operation is idempotent, cached, or rate-limited, and provides only high-level description of return values without structural details.

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 consists of three efficiently structured sentences: the first defines the core action, the second provides business context for selection, and the third states the workflow prerequisite. Every sentence earns its place with no redundant or filler content.

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?

Despite lacking an output schema, the description partially compensates by explaining that the tool returns 'career-level tiers and their product IDs'. Combined with the explicit workflow integration (prerequisite for place_order), this provides sufficient context for a zero-parameter lookup tool, though specific return structure details would strengthen it further.

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 input schema contains zero parameters. Per evaluation rules, zero-parameter tools receive a baseline score of 4. The description appropriately does not mention parameters since none exist.

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 explicitly states the tool retrieves 'career-level tiers and their product IDs' using the specific verb 'Get'. It distinguishes itself from sibling tools by explaining its role as a prerequisite for place_order (getting productId), clearly differentiating it from get_credits.

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 provides explicit workflow guidance: 'You must call this before placing an order to get the correct productId.' It also includes selection criteria ('customer should pick the tier that best matches where they are in their career'), giving clear context on when and how to use the results.

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?

With no annotations provided, the description carries the full burden, effectively disclosing key behavioral traits: processing time (~15 minutes), notification mechanism (two SMS messages), and cost (1 credit). It omits idempotency or error handling details.

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?

Four tightly constructed sentences with zero waste: purpose, timing, notifications, and cost. Information is front-loaded and every sentence 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?

Given the 6-parameter complexity and lack of annotations/output schema, the description is reasonably complete, covering the user journey (order → SMS confirmation → SMS completion). It could strengthen by noting the prerequisite check for credits.

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 input schema has 100% description coverage, establishing a baseline of 3. The description text does not add parameter-specific semantics (e.g., explaining markdown format or productId sourcing), relying entirely on the schema.

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 a specific verb ('Place') and clear resource ('order for a tailored CV and cover letter'), immediately distinguishing it from the read-only sibling tools get_credits and get_pricing.

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 mentions 'Costs 1 credit per order,' implying a prerequisite to check credits, but lacks explicit guidance on when to use versus alternatives or a required workflow (e.g., calling get_pricing first to obtain the productId).

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