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Configure Memory

configure_profile_remember_many

Use this when the user asks to save several facts at once, or approves a list of facts you proposed. Saves each entry as a separate memory in the user's Configure profile, in one call. Send only facts the user asked to save or approved, each a short standalone statement about the user. If the user asks to review first, show the list and wait for their approval before calling. Use configure_profile_remember for a single fact. Accepts 1 to 100 facts per call, up to 1,000 characters each and 20,000 in total; send a longer approved list as several calls. It is not for passwords, keys, payment or health details, government identifiers, identity documents, sensitive personal attributes (race, religion, politics, sexuality, biometrics or genetics), or other people's personal data; the server's pattern checks are a backstop, not a complete filter, so these are left out before calling. Optional box files a fact under a category. Additive: it never changes or deletes existing memories. Returns a result for each entry and counts of saved, already_saved, refused and failed. Report those counts accurately, retry only failed entries, and never say the whole list was saved when some entries were refused or failed. Use configure_profile_import instead when the user supplies raw material rather than a list of facts: a note, a document, or an export from another assistant.

Input Schema

NameRequiredDescriptionDefault
factsYesShort standalone facts the user asked to save or approved. At most 20,000 fact characters in total.

Output Schema

NameRequiredDescriptionDefault
countsYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / facts / maxItems
      Previous value: -25New value: +100
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the annotations, it discloses that the operation is additive and never mutates existing memories, the batch limits (1-100 facts, 1,000 chars each, 20,000 total) with a strategy for longer lists, the content-safety exclusions with the caveat that server pattern checks are only a backstop, and that results may include refused entries. That last point meaningfully affects how an agent should report outcomes.

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?

It is front-loaded with the trigger, then constraints, then alternatives, which is the right ordering. It is on the long side and the reporting-guidance sentence could be trimmed, but nearly every sentence carries actionable information.

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?

The tool is a batch mutation with content restrictions, so the description covers batching limits, exclusions, approval flow, and result handling. An output schema exists, yet the description of per-entry results and saved/already_saved/refused/failed counts adds the reporting rule an agent needs to avoid misstating success.

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 coverage is 100%, so baseline is 3, but the description adds real meaning: what a valid entry is ("a short standalone statement about the user"), the significance of the optional box field ("files a fact under a category"), and the aggregate character budget that the schema only states for the array. Modest but genuine value on top of the 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 states a specific verb and resource ("Saves each entry as a separate memory in the user's Configure profile, in one call") and explicitly differentiates from two siblings, naming configure_profile_remember for a single fact and configure_profile_import for raw material. An agent can pick this tool without opening any schema.

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?

It names concrete trigger conditions (the user asks to save several facts, or approves a proposed list), an approval gate ("If the user asks to review first, show the list and wait for their approval before calling"), and two named alternatives with the condition that selects each. Both when-to-use and when-not-to-use are covered.

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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