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update_user_preference_topic

Idempotent

Update a user's preference for a specific subscription topic (opt in, opt out, or set channel preferences).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesPreference status
user_idYesThe user ID
topic_idYesThe subscription topic ID
tenant_idNoUpdate the preference for this tenant context only
custom_routingNoCustom channel routing order
digest_schedule_idNoPut the user on one of the topic's digest schedules. Pass null to clear their choice and fall back to the default schedule.
has_custom_routingNoWhether custom channel routing is set

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / digest_schedule_id
      Added value: +{
      +  "description": "Put the user on one of the topic's digest schedules. Pass null to clear their choice and fall back to the default schedule.",
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
    • addedInput schema / properties / tenant_id
      Added value: +{
      +  "description": "Update the preference for this tenant context only",
      +  "type": "string"
      +}
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations declare readOnlyHint=false, idempotentHint=true, destructiveHint=false, and the description is consistent with these (no contradiction). The description adds that the update can be an opt in/out or channel preference change, which provides a little behavioral context beyond the schema. However, it does not disclose side effects, permission requirements, or return behavior, so it adds only modest value over the annotations.

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 a single sentence that front-loads the verb and resource, followed by a parenthetical clarifying the scope. It is concise and free of fluff, though it could be slightly more structured to separate the action from the specific cases.

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

Completeness3/5

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

For a 7-parameter mutation tool with no output schema, the description is minimal. It does not mention what the function returns, any prerequisites, or how it differs from related tools like update_tenant_preference or replace_preference_topic. However, the schema fully documents all parameters and the annotations cover the safety profile, so it is adequate but not thorough.

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

Parameters3/5

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

Schema coverage is 100%—all 7 parameters are documented in the input schema. The description's mention of 'opt in, opt out, or set channel preferences' loosely maps to the status enum and custom_routing, but it does not provide any parameter-specific details beyond what the schema already supplies. Baseline of 3 is appropriate given full schema coverage.

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

Purpose4/5

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

The description clearly states a specific verb (update) and resource (user's preference for a specific subscription topic), and enumerates the action types (opt in, opt out, set channel preferences). It distinguishes itself from bulk operations by saying 'a specific' topic, but it does not explicitly name sibling tools like get_user_preference_topic or delete_user_preference_topic, so it lacks explicit sibling differentiation.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. It does not mention that bulk updates should use bulk_update_user_preferences or that reads should use get_user_preference_topic. The only contextual clue is the word 'specific', which implies a single topic but no explicit when/when-not guidance.

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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