Get full contact details including all related data in one call: contact methods, addresses, food preferences, custom fields, tags, relationships, recent notes, recent activities, life events, active reminders, open tasks, recent gifts, active debts, and debt summary
| Name | Required | Description | Default |
|---|---|---|---|
| contact_id | Yes | The contact ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It lists broad return categories (contact methods, activities, gifts, debts), which is helpful, but it omits behavioral details such as the definition of 'recent', whether empty lists are omitted, or inherent performance/authorization implications for a heavy aggregate call.
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 one sentence with a strong front-loaded purpose, followed by a long list of data types. The list is necessary to convey the aggregate scope, so the length is justified and the structure reads efficiently.
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?
Without an output schema, the description compensates by enumerating 14 categories of returned data, giving a solid expectation of the response. The single required parameter is simple, and the description is largely complete, though caveats about empty lists or the meaning of 'recent' could add further clarity.
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 a 100% description for the only parameter, contact_id, so the baseline is 3. The description adds no extra semantics beyond indicating that the returned details belong to the specified contact.
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 ('Get') and resource ('full contact details') while enumerating the exact data categories included, making its purpose unmistakable. It clearly distinguishes itself from sibling tools like contact_list (which likely returns summaries) and domain-specific getters like food_preferences_get.
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 phrase 'including all related data in one call' provides clear context for when to use this tool—when a complete contact snapshot is needed, avoiding multiple sibling calls. It does not explicitly list exclusions or alternatives, but the usage intent is 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 are clearly distinct by entity, but contact_get and contact_timeline overlap significantly, and debt_manage's action='list' duplicates what other entities do with a dedicated list tool. Descriptions are detailed enough to resolve most ambiguity, though.
Tool names are mostly snake_case and readable, but they mix conventions: noun_verb (contact_create), verb_noun (batch_create_activities), and descriptive phrases (contacts_needing_attention). The noun_manage pattern is dominant, but the lack of uniformity makes the naming less predictable.
With 42 tools, the surface is very large, even for a full-featured CRM. Many tools bundle multiple actions, but the sheer number forces an agent to consider many options, increasing selection difficulty and cognitive load.
The server provides comprehensive CRM coverage: contacts, activities, notes, tasks, reminders, gifts, debts, relationships, tags, custom fields, notifications, settings, and exports. It supports batch operations, duplicate detection, merge, and special queries, leaving few if any obvious gaps.