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list_preference_logs

Read-only

List preference changes, newest first. Each entry is one change a user made to one subscription topic, with the value before it where there was one. Pass user_id to answer "when did this user opt out, and of what?"; omit it to read the whole environment. Page with paging.cursor while paging.more is true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoEntries per page, 1 to 100. Defaults to 25.
sinceNoOnly changes at or after this time, as an ISO 8601 date or date-time. A date alone is the start of that day in UTC.
cursorNopaging.cursor from a previous response
user_idNoReturn only this user's changes. Omit to read every change in the environment.
tenant_idNoNarrow to the changes the user made in one tenant context. Requires user_id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds genuinely useful behavior beyond that: newest-first ordering, one entry per user-per-topic change, inclusion of the prior value 'where there was one', and cursor-based paging driven by paging.more.

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

Conciseness5/5

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

Three sentences, each earning its place: identity and ordering first, then filter semantics, then pagination. Front-loaded and free of redundancy.

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?

With no output schema, the description carries the burden of describing the return shape, and it does: entries are one preference change per topic with the prior value when one existed, plus how to page. Nothing needed to call this correctly is missing.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description goes beyond the schema by framing what user_id actually answers (an opt-out audit question) and contrasting it with omitting the parameter to read the whole environment, though tenant_id receives no extra explanation.

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?

States a specific verb and resource ('List preference changes') plus ordering ('newest first'), and the second sentence defines the unit of an entry, which separates this audit-log tool from siblings like get_user_preferences or list_preference_topics.

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?

Gives explicit when-to-use guidance for the key filtering mode ('Pass user_id to answer "when did this user opt out, and of what?"; omit it to read the whole environment') plus paging instructions. It stops short of naming a sibling tool as the alternative, so it is clear context rather than a full when/when-not/alternatives statement.

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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