Check eligibility for the Costco partner service and Shop Card reward (Executive membership + a settled loan). Indicative check only.
Args:
is_costco_member: Whether the person holds a current Costco membership.
membership_type: e.g. "Executive" or "Gold Star" (optional).
| Name | Required | Description | Default |
|---|---|---|---|
| membership_type | No | ||
| is_costco_member | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It states it is an 'indicative check only,' hinting at non-definitive results. It could be more explicit about data handling or read-only nature, but is reasonably transparent.
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 is concise, with a clear two-paragraph structure. The Args section is integrated efficiently. Could be slightly more compact, but no wasted sentences.
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?
The tool has no output schema, so the description should ideally clarify the return value (e.g., boolean or eligibility status). It does not, leaving agents to guess the output format. Otherwise, it covers input parameters and purpose adequately.
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 0%, but the description's Args section explains both parameters with examples ('Executive' or 'Gold Star'), adding meaning beyond the bare schema. It compensates well for the lack of schema descriptions.
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 eligibility for the Costco partner service and Shop Card reward, specifying conditions (Executive membership + settled loan). It is distinct from sibling tools like calculate_repayments or create_enquiry.
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 clear context for when to use the tool, and sibling tools are sufficiently different to imply appropriate usage. However, it lacks explicit 'when not to use' or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of the mortgage process: repayment calculation, Costco eligibility, loan type comparison, enquiry submission, borrowing power estimation, and rate guidance. There is no functional overlap.
All tool names follow a consistent verb_noun pattern (e.g., calculate_repayments, check_costco_eligibility, compare_loan_types), using lowercase with underscores.
With 6 tools, the set is well-scoped for a mortgage advisory server, covering key pre-application steps without being overly large or too sparse.
The tools cover the core pre-application workflow: calculation, borrowing power, rate guidance, comparison, eligibility, and enquiry. A minor gap is the lack of tools for existing loan management or detailed offer comparison.