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STEM — Persistent AI Memory

Save opted-in context to STEM memory

remember_automatically

Save useful, non-sensitive distilled context to the authenticated user's STEM account for future sessions and compatible assistants connected to that same account. First call memory_status with an empty object: only automaticSavingAllowed exactly true permits a best-effort automatic save, subject to host confirmations and the user's no-save instructions. The server checks current consent on every write. Returns a new numeric memory ID, source, type and autolinked IDs; retries can duplicate saves. This does not import unsaved conversations, capture every chat, browse the web or access other users' data. Never store whole transcripts or secrets, or bypass host confirmations. Use remember for explicit user save requests.

Input Schema

NameRequiredDescriptionDefault
tagsNoOptional topic labels stored with this memory; these are not access permissions.
textYesNon-empty distilled context to save for later use: a fact, preference, decision, idea, question or note. Preserve relevant attribution; exclude secrets and whole transcripts.
typeNoCategory of the saved context (default note).
sourceNoOrigin label for the supplied context (default notes). Labels such as claude, chatgpt or web do not connect to, fetch from, or import that service.
autolinkNoIf true, also create relates links to up to three related memories from a pool of up to 300 saved memories in the same account (default false).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations: consent is re-checked server-side on every write, saves are best-effort, retries can duplicate an entry, and it enumerates what is returned (memory ID, source, type, autolinked IDs). It also discloses negative scope (no transcript import, no browsing, no cross-user access), which annotations alone could not convey.

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?

Front-loads the action and the consent prerequisite, and each subsequent sentence carries a distinct constraint or exclusion. It is denser than typical, but no sentence is filler; the prohibition list is the only mildly repetitive part.

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?

For a non-idempotent mutation gated on consent, the description covers prerequisite, call-time checks, failure/duplication behavior, return shape (compensating for the absent output schema), and prohibited inputs. An agent has everything needed to decide whether and how to call it.

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 the per-field semantics are already documented; the description nonetheless adds constraint-level guidance on what may be passed ('never store whole transcripts or secrets') and notes that autolink results surface as autolinked IDs in the response. Tags, type and source are left entirely to 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?

States a specific verb and resource (save distilled context to the user's STEM account) and scopes it to opted-in automatic saving. It is clearly separable from siblings by explicitly naming memory_status as a prerequisite and remember as the explicit-save alternative.

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?

Gives an explicit precondition ('First call memory_status with an empty object: only automaticSavingAllowed exactly true permits...'), the conditions that block a save (host confirmations, no-save instructions), and the alternative tool for explicit requests ('Use remember for explicit user save requests').

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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