browse_genresList all 35 Czech audiobook genres with audiobook counts. Discovery entry point — agents enumerate genres before drilling into a specific one.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds concrete details (exactly 35 genres, includes counts), which provides behavioral context beyond the annotations. No contradictions.
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, efficiently front-loading the action and resource in the first sentence, with usage guidance in the second. No wasted words.
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 no parameters, an output schema (true), and annotations covering safety, the description is complete. It specifies the exact count (35) and that counts are included, which is sufficient for a simple list tool.
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?
With zero parameters, the baseline score is 4. The description does not need to add parameter info, and it appropriately focuses on the tool's output.
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 ('List') and resource ('all 35 Czech audiobook genres with audiobook counts'), clearly distinguishing it from sibling tools like search_audiobooks or get_audiobook_rankings.
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 explicitly states it as a 'discovery entry point' and advises agents to 'enumerate genres before drilling into a specific one,' providing clear usage context. However, it does not mention when not to use it or list alternatives.
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 have distinct purposes, but `compare_all_offers` and `find_cheapest_offer` overlap in pricing queries. Descriptions clarify the difference (full table vs. cheapest only), so ambiguity is low. Similarly, `search_audiobooks` and `search_by_filters` are distinct in input style.
All tools follow a consistent verb_noun pattern in snake_case (e.g., `browse_genres`, `get_audiobook`, `search_by_filters`). No mixing of conventions or irregular naming.
13 tools cover browsing, searching, detailed info, price comparison, analytics, and profiles. The number is well-balanced for the catalog's scope—neither sparse nor excessive.
The tool set covers key workflows: discovery, search, details, price comparison, trends, rankings, and partner info. Minor gaps like user reviews or advanced filtering (e.g., partner filter in V2) are acceptable for a focused catalog.