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Glama
M-T-D-N

agentmemory-codex-windows

memory_slot_create

Create a new labeled, size-limited memory slot to persist project or global context; pinned slots are injected and duplicate labels are rejected within scope.

Instructions

Persist a new size-limited context slot, returning {success,slot}. label is lowercase, starts with a letter, uses letters/digits/underscores and is at most 64 characters. sizeLimit is an integer from 1 to 20000; content must fit. Rejects duplicate labels within the selected scope; a project slot can shadow a global one. Pinned slots participate in context injection. Use memory_slot_replace for existing content; creation records an audit entry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelYesSlot label — lowercase, starts with letter, [a-z0-9_]
scopeNo'project' (default) or 'global' (shared across projects)
pinnedNo'false' to exclude from context injection; default true
contentNoInitial content (default empty)
sizeLimitNoMax chars (default 2000, hard cap 20000)
descriptionNoWhat this slot is for

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0-preview.14-glama.1

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: duplicate-label rejection within scope, project-shadows-global semantics, pinned-slot inclusion in context injection, audit-entry creation, and the return shape {success,slot}. These are meaningful behavioral traits an agent could not infer from the schema.

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?

Front-loaded with the action and return value, followed by tightly packed constraint and behavior clauses. Every sentence adds distinct information (format rules, collision behavior, pinning, audit), with no filler.

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 6-parameter mutation with no output schema, the description supplies the return shape, defaults context, collision/scoping semantics, and side effects. Nothing critical an agent needs to invoke it 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 coverage is 100%, so baseline is 3, but the description adds real constraints beyond the schema: label max length of 64 characters, and sizeLimit as an integer bounded 1–20000 with content required to fit. It reinforces meaning rather than merely restating 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 opens with a specific verb+resource ("Persist a new size-limited context slot") and explicitly contrasts with the sibling memory_slot_replace for existing content. An agent can distinguish this from memory_slot_append, memory_slot_get, and memory_slot_list from the text alone.

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?

It clearly routes the agent to memory_slot_replace when content already exists, establishing the create-vs-replace boundary. It does not cover other alternatives or explicitly state when-not to use it, but the primary confusion case is handled.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.