aisensy_find_contactLook up a contact by phone number: id, name, tags, attributes, opt-in/chat state and last activity. 404 means no such contact. GET /project/{project_id}/contact?action=FetchContact&mobile_number=.
| Name | Required | Description | Default |
|---|---|---|---|
| phone_number | Yes | Phone number with country code, e.g. 919876543210 (digits; a leading + is dropped). |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds critical behavioral information not captured in the schema or annotations, specifically detailing the fields returned (e.g., opt-in/chat state) and the specific error code mapping (404 means no contact found).
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 extremely concise and highly efficient. It includes the key functional definition, the result set, and the error condition in two clear statements.
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?
The tool description is complete for the agent. By listing the specific fields and the 404 error behavior, the agent knows exactly what to expect from the tool's execution even without a formal output schema.
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 schema description coverage is 100%, so the parameter semantics are well-covered structurally. The description adds no semantic value beyond what the schema already provides for the 'phone_number' field, matching the baseline for high coverage.
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 purpose is stated immediately and clearly: 'Look up a contact by phone number.' It specifies the resource (contact) and the action (lookup), distinguishing it from siblings like get_contact which implies a different search key.
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 exactly what information the agent receives (id, tags, attributes, etc.), indicating when this tool should be preferred over a basic lookup. While it doesn't explicitly name alternatives, the scope of returned data provides strong usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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