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damientilman

Mailchimp MCP

update_segment

Update a Mailchimp segment's name or dynamic filter conditions. Modify only specified fields without affecting others.

Instructions

Update a segment's name or dynamic filter conditions.

Only provided fields are updated. Idempotent: re-applying the same name is safe. Cannot change a segment from static to dynamic or vice versa. Use add_members_to_segment or remove_members_from_segment to manage static segment membership instead.

Authenticated via API key. Max 10 concurrent requests. Respects read-only and dry-run modes. Returns 404 error if segment_id is invalid. Providing match without conditions_json is ignored.

Args: list_id: Audience/list ID (10-char alphanumeric, e.g. 'abc123def4'). Obtain from list_audiences. segment_id: Segment ID to update (numeric string, e.g. '12345'). Obtain from list_segments. name: New display name for the segment. match: Condition match type for dynamic segments: 'all' (AND) or 'any' (OR). Must be provided together with conditions_json. conditions_json: JSON string of conditions array. Must be provided with match.

Returns: JSON with id, name, member_count, type ('static'/'saved'), options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes
segment_idYes
nameNo
matchNo
conditions_jsonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, description carries full burden. Discloses authentication, rate limits, dry-run mode, 404 error, and ignored parameter case. Could mention impact on existing segment membership when changing conditions, but overall good.

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?

Well-structured with summary, bulleted Args, and Returns. Some repetition (idempotent and only provided fields), but concise given the amount of detail. Slightly long but not wasteful.

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?

Covers all aspects: parameters, behavior (idempotent, errors), constraints (cannot change type), security (API key), and return values. Output schema exists and description specifies return shape. No obvious gaps.

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 description coverage is 0%, but description fully explains each parameter: examples for list_id and segment_id, optional nature, match 'all'/'any' values, and necessity of pairing match with conditions_json. Adds significant value beyond 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?

Description clearly states 'Update a segment's name or dynamic filter conditions', specifying verb and resource. Differentiates from sibling tools like add_members_to_segment and create_segment by focusing on update of name/filter conditions.

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

Usage Guidelines5/5

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

Explicitly states when not to use (cannot change static/dynamic) and directs to add_members_to_segment/remove_members_to_segment for membership management. Also notes idempotency and parameter co-dependency (match and conditions_json together).

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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