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kylastech

Kylas CRM MCP Server

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by kylastech

update_lead

Update a lead's fields in Kylas CRM by providing lead ID and field values. Merges changes while leaving other fields unchanged.

Instructions

Update a lead in Kylas CRM. Fetches the lead first, merges your field_values into it, then PUTs the full body. Same field_values format as create_lead. Call get_lead_field_instructions first for API names and custom field internal names. For owner: use lookup_users to get the user ID, then pass ownerId: in field_values.

lead_id: The lead ID to update (e.g. from search_leads or search_leads_by_term results). field_values: Map of field identifier to value (same as create_lead: firstName, lastName, email, phone with phone_country_code, customFieldValues, picklist Option IDs, date/datetime in UTC ISO, etc.). These are merged over the existing lead; other fields are left unchanged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lead_idYes
field_valuesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description fully handles transparency. It explains the fetch-merge-PUT pattern, that other fields are left unchanged, and provides details on field handling. It could mention that this is a mutation (update) but the action itself implies it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: start with high-level purpose, then details on prerequisites and parameters. Each sentence adds value, though slightly dense. Not overly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two parameters, no annotations, and an existing output schema, the description covers the main aspects: what the tool does, how it works, parameter details, prerequisites, and special cases. It is comprehensive and leaves little ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must explain parameters. It provides detailed meaning for lead_id (source e.g., search_leads) and field_values (format, examples like phone with country code, custom fields, picklists). This adds significant value beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates a lead in Kylas CRM, using precise verbs ('Update') and specifying the resource ('lead'). It distinguishes itself from siblings like create_lead (create vs. update) and get_lead (read vs. write).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit prerequisites (call get_lead_field_instructions first, for owner use lookup_users) and references create_lead for field format. It does not explicitly state when not to use it, but the context is clear enough. Lacks explicit exclusions.

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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