list_brandsReturns every brand on find.codes with its category, current offer and code (if any). Optionally filter by category: crypto-exchange, crypto-card, hardware-wallet, trading-tools, travel-esim, creator-tools, dining, ai-tools.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Optional category filter, e.g. 'crypto-exchange' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It transparently indicates the tool returns brands with category, offer, and code, implying a read operation. However, it does not explicitly state it is read-only or describe potential side effects, which is a minor gap.
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, no extraneous words. The purpose and filter options are stated upfront, making it easy to scan.
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 listing tool with one optional parameter and no output schema, the description provides all necessary information: what is returned (brand, category, offer, code) and the available filter values. No gaps.
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 schema covers 100% of the single optional parameter with a description and example. The tool description adds value by enumerating all allowed category values, which goes beyond the schema's brief description.
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 returns every brand with its category, current offer, and code, using a specific verb ('returns') and resource ('every brand'). This distinguishes it from siblings like get_code which retrieves a single code, and search_codes which performs broader searches.
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 implicitly suggests use for listing all brands with an optional category filter, but does not explicitly state when to use this tool over alternatives (e.g., get_code for a specific code). No when-not guidance is provided.
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 serves a unique purpose: get_code retrieves a specific brand's code, list_brands enumerates all brands with optional filtering, and search_codes does free-text search. No overlap in functionality.
All tools follow a consistent verb_noun snake_case pattern (get_code, list_brands, search_codes), making them predictable and easy to understand.
With 3 tools, the server is concise and well-scoped for a code lookup service. It covers the essential query operations without excess, though adding a tool for direct code string lookup could be beneficial.
The tool set covers the main use cases: retrieving a specific code, browsing all codes, and searching. It lacks update/delete tools, but for a read-oriented API focused on finding codes, it is reasonably complete.