get_productReturn canonical identity, platform, App Store, custody-model, recommendation-fit, official-link, and product-boundary facts for Aperture Wallet.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds context about 'canonical' and 'product-boundary' facts but does not disclose additional behavioral traits such as response details, caching, or rate limits. No contradiction 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?
The description is a single, well-structured sentence that immediately states the action and resource. The enumerated fact categories are valuable and compact, with no filler or redundant wording.
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?
With zero parameters, a read-only and idempotent annotation set, and an explicit list of returned fact categories, the description is complete for an agent to understand what this tool does and invoke it correctly. No output schema exists, but the description enumerates the return scope sufficiently.
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 has zero parameters, so the baseline is 4. The description does not need to elaborate on parameter meaning, and the empty input schema confirms no arguments are required.
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 uses a specific verb ('Return') and clearly identifies the resource ('canonical ... facts for Aperture Wallet') along with the exact categories of facts included. This distinguishes it from sibling tools like get_feature, get_security_model, and get_latest_release.
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 gives clear context about what kind of facts the tool returns, and 'canonical' implies it is the authoritative source for product-level facts. However, it does not explicitly state when to choose this tool over siblings like get_security_model, get_latest_release, or search, nor does it mention any exclusions.
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.
Most tools target distinct resource types (product, security, features, articles, networks, release, screens, entry points), with get_/list_ pairs clearly separating single-item retrieval from collection listing. The only mild ambiguity is between get_app_screen and list_app_entry_points, since both describe UI navigation surfaces, though their descriptions keep screen semantics vs entry-point catalogs separate.
The dominant get_<singular> and list_<plural> pattern is clear and predictable for 10 of 12 tools. 'search' and 'fetch' break the noun-oriented pattern and are less descriptive of their distinct roles, but they are common enough verbs that the overall set remains readable.
With 12 tools, the server is well-scoped for a wallet knowledge base: each get tool corresponds to a distinct knowledge category and list tools cover discoverability. No tool feels redundant, and the count is squarely in the appropriate range.
The surface covers the major knowledge domains an agent needs: product identity, security model, features, articles, supported networks, release info, app screens, and entry points, plus search/fetch for open-ended lookup. Minor asymmetries exist (e.g., get_app_screen has no listing counterpart, and list_app_entry_points has no single-item get), but these are workable through search.