get_websiteFetch safe metadata for one website owned by the authenticated Supovia organization. Organization ids, agent prompts, credentials, integration configuration, and arbitrary metadata are never returned.
| Name | Required | Description | Default |
|---|---|---|---|
| idOrName | Yes | Website id or exact name |
| Name | Required | Description | Default |
|---|---|---|---|
| status | Yes | ||
| website | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description goes beyond by detailing which sensitive fields are excluded (org ids, prompts, credentials, integration config, arbitrary metadata) and uses the term 'safe metadata,' providing behavioral guarantees not present in the annotations.
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 with no redundancy. The core action and scope come first, followed by a clear exclusion list. Every word adds value; the structure is efficient and 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?
With a single well-documented parameter, an output schema available, and annotations covering the safety profile, the description fully specifies what the tool does and what it never returns. An agent has all necessary information to invoke it correctly without additional inference.
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 fully describes the parameter ('Website id or exact name'), covering 100% of schema description. The description adds contextual meaning by clarifying that the website must be owned by the authenticated organization, which helps interpret the parameter's domain. This is a modest addition beyond the schema.
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 a specific verb ('Fetch') and resource ('safe metadata for one website') plus a scope restriction ('owned by the authenticated Supovia organization'). It explicitly lists what is never returned, which distinguishes it from broad list tools like list_websites and other getters like get_conversation.
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 specifies the context (one website owned by the authenticated org) and implies that this tool is for single-website retrieval, contrasting with list_websites for all websites. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.
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 targets a distinct action: retrieving single resources (get_conversation, get_document, get_website), listing sets (list_*), searching (search_documents), mutating state (resolve_conversation, send_message), and rendering views (show_customer_inbox, show_support_overview). Even the two inbox-related tools are clearly separated: one opens and counts, the other refreshes a specific conversation. No two tools could be easily confused.
All tool names follow a consistent verb_noun pattern with clear verbs: get, list, search, open, resolve, send, show. The naming is uniform across the set, with no mixed conventions (e.g., camelCase or vague verbs like 'process'). The pattern makes it predictable for an agent to infer tool purposes.
With 14 tools, the server is well-scoped for a customer support/support-documentation domain. Each tool covers a distinct responsibility without redundancy, and the count is within the ideal 3–15 range. There is no bloat or triviality.
The tool surface covers the core workflows: listing and retrieving conversations, resolving or sending messages, reading and searching documents, and listing websites/campaigns. Minor gaps exist (e.g., no document update/delete, no campaign creation/send), but these appear intentionally read-only for safety and the main support operations are well covered.