list_productsList active products from the Hermes Plant catalog
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes | True when the upstream storefront call returned a 2xx response | |
| httpStatus | Yes | Upstream HTTP status code | |
| paymentRequired | No | True when the response is an x402 HTTP 402 payment challenge |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation read-only and idempotent, so the safety profile is covered. The description adds valuable context by specifying that only active products from the Hermes Plant catalog are returned, giving a concrete behavioral filter beyond the annotations. No return-format detail is needed since an output schema exists.
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 a single, front-loaded sentence that is concise and information-dense. It contains no filler or redundant phrasing, earning a perfect score.
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 (no parameters, output schema present, read-only annotations), the description is fully sufficient. It identifies the exact scope (active products in the Hermes Plant catalog) and all other contextual information is covered by annotations and the output schema.
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 tool takes zero parameters, so the description carries no parameter burden. The baseline of 4 applies because there are no parameters to describe, and the schema has no properties, so there is no gap to compensate for.
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 action (list), the resource (products), and a specific qualifier (active products from the Hermes Plant catalog). This distinguishes it from sibling tools like get_product, which retrieves a single product.
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 by indicating that the tool lists active products, implying it is used when a catalog listing is needed. However, it does not explicitly mention alternatives such as get_product for single-item lookups, so it lacks explicit exclusions or when-not-to-use guidance.
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 has a clear, distinct purpose. Financial tools (bond, cashflow, deal, options, portfolio, wallet, waterfall) each target a specific analysis type, email tools are batch vs single, and e-commerce tools are separate. No two tools could be easily confused.
Most tools follow a noun_verb pattern (e.g., bond_analyze, emailguard_validate), but there is some inconsistency: some use verb_noun (get_product, list_products) and brand names like cashflowlens_analyze break the pattern slightly. Overall, it is still readable and mostly predictable.
With 19 tools spanning finance, email, security, and e-commerce, the count is slightly high but reasonable for a pay-per-use server offering diverse deterministic analytics. Each tool serves a distinct function, and the number is not overwhelming.
The set covers major financial analysis types, email validation, and basic e-commerce operations. Minor gaps (e.g., no tool for portfolio rebalancing or more advanced email features) exist, but the core advertised services are well-covered.