list_partnersList active retail partners with audiobook counts. Required for transparency / disclosure when an agent needs to explain HOW audioknihy.cz monetises recommendations (we are an affiliate aggregator, not a retailer).
| 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 provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context about monetization disclosure beyond what annotations convey, without contradiction.
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 two sentences, front-loaded with the action, and every word adds value. No redundancy or fluff.
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 zero parameters, comprehensive annotations, and an existing output schema, the description fully covers the tool's purpose and usage context. Nothing is missing.
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, schema coverage is 100%. The description adds no parameter info, but none is needed. Baseline 4 is appropriate for a parameterless tool.
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 states a specific verb ('List') and resource ('active retail partners with audiobook counts'), making the tool's purpose clear. It is clearly distinct from sibling tools like search_audiobooks or get_audiobook, which focus on different operations.
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 explicit usage context: 'Required for transparency / disclosure when an agent needs to explain HOW audioknihy.cz monetises recommendations'. While it lacks explicit when-not guidance, the context is sufficiently clear.
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.