get_source_infoReturns what Cellarion is, the version this instance is running, the open-source repository, and the license. Call this when the user asks what Cellarion is, which version they are on, whether it is open source, where to find / contribute to the code — or how to support the project.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations: it specifies the exact returned information (Cellarion, version, repository, license). Annotations already indicate read-only and non-destructive behavior, so the description complements them 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?
Two sentences that front-load the purpose and usage. Every sentence earns its place; no fluff or redundancy.
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, description fully covers what the tool returns. Includes common user queries (open source, support). Context of sibling tools (wine-related) makes this independent tool complete.
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?
No parameters exist, so schema description coverage is 100%. The description adds no param info, which is appropriate. Baseline for zero parameters is 4.
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 specific information: what Cellarion is, version, repository, and license. It uses specific verbs and resources, distinguishing it from sibling tools like get_wine or find_similar_wines.
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 lists when to call the tool (user asks about Cellarion, version, open source, etc.). It lacks explicit when-not-to-use or alternatives, but given the sibling context, the usage is clear and well-guided.
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 addresses a distinct concern: registry search, wine detail, vintage-specific drink windows, similarity recommendations, guide listing, guide reading, and server metadata. No two tools serve the same purpose, and the descriptions clearly indicate when to use each.
Most tools follow a consistent verb_noun pattern (list_guides, read_guide, search_registry, get_wine, get_source_info, find_similar_wines). 'drink_window_for' is an outlier, using a noun phrase instead of an imperative verb, which introduces a minor inconsistency.
With seven tools, the server is well-scoped and avoids bloat. Each tool provides a distinct capability, and the count is appropriate for a wine registry server covering search, details, drink windows, similar wines, guides, and metadata.
The core registry workflow is well covered: search_registry for identification, get_wine for details, drink_window_for for aging advice, and find_similar_wines for recommendations. However, multiple descriptions reference search_bottles for user-owned bottles, yet that tool is not provided, leaving a notable gap for user-specific queries.