get_listFull contents of a saved list: sponsors, podcasts (Pro plans), categories, and contacts. Contacts follow the same masking and reveal rules as list_sponsor_contacts, including the deduplicated internal usage record on included-contact plans (no credits are charged).
| Name | Required | Description | Default |
|---|---|---|---|
| list_id | Yes | The list's id (from list_lists or create_list) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations: it explains that contacts follow masking/reveal rules and that no credits are charged for deduplicated internal usage. Annotations already indicate idempotency and non-destructiveness, so the description enriches behavioral understanding.
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 convey the tool's purpose and key behavioral detail. No unnecessary words; the main content is front-loaded.
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 output schema, the description adequately explains the return contents and special contact behavior. Missing elements like pagination or error handling for missing list_id are minor, but the tool is simple and the description covers the core.
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 input schema already provides 100% coverage for the single parameter list_id, including a description referencing list_lists or create_list. The tool description does not add further meaning to the parameter beyond what the schema offers.
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 'Full contents of a saved list' and enumerates the specific components: sponsors, podcasts, categories, and contacts. This directly addresses what the tool does and differentiates it from siblings that return individual elements (e.g., get_podcast, get_category).
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 mentions that contacts follow similar rules as list_sponsor_contacts, implying when to use this tool for a comprehensive view versus a contacts-only retrieval. However, it does not explicitly state when to use this tool vs alternatives or provide 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 have clear, distinct purposes. Overlap exists between search/search_sponsors and fetch/get_sponsor, but descriptions clarify the different use cases (deep-research compatibility vs. full structured queries). Overall, an agent can reliably differentiate tools.
The naming convention is predominantly verb_noun (e.g., create_list, get_sponsor), but two tools (fetch, search) are single verbs without a noun, breaking consistency. This introduces minor confusion about their scope.
17 tools is a reasonable number for a podcast sponsorship database, covering search, retrieval, list management, and contact operations. It's not overly heavy nor too thin for the domain.
The tool surface covers primary operations: searching sponsors/podcasts, retrieving details, managing lists, and handling contacts. Minor gaps exist (e.g., no tool to update sponsor data, but that's likely read-only), but core workflows are well-supported.