Scan for potential duplicate contacts using name, email, and phone matching. Returns pairs of contacts that may be duplicates with the reason for the match.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. It discloses the matching criteria (name, email, phone) and the output (pairs with reasons), which gives the agent a clear picture of expected behavior. The word 'scan' implies a non-destructive read operation, but it does not explicitly state that no data is modified, nor describe any limits or edge cases.
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 long, directly front-loaded with the main action, and every word contributes value. No redundant information.
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?
For a zero-parameter tool with no output schema, the description is complete: it explains the action, the matching methods, and the return format. The only minor gap is the lack of an explicit statement about global scope or read-only behavior, but 'scan' and 'returns' convey this adequately.
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 tool has zero parameters, so the description does not need to explain parameter semantics. According to the rubric, the baseline is 4; the description appropriately omits any parameter details.
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 'Scan for potential duplicate contacts' using name, email, and phone matching, which is a specific verb + resource + method. It distinguishes itself from sibling tools like contact_merge (which would act on duplicates) and contact_list (which lists all contacts).
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?
There is no explicit guidance on when to use this tool vs alternatives. The purpose implies deduplication workflows, but it does not mention that this should precede contact_merge or that it scans the entire contact database. Lacks exclusions or alternative references.
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.