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Glama

store_memory

Persist one explicitly approved fact, preference, project detail, decision, environment note, or pitfall with scope, tags, and source references so durable context survives sessions.

Instructions

WRITE. Store one memory. Precondition: the user explicitly asked to remember it or confirmed a fact you proposed; never store silently. kind: fact, preference, project, decision, environment, pitfall. scope: project (default), branch (true only on this branch) or checkout (true only for this clone). global_memory=true for facts that hold everywhere. refs: pointers (§15) to the source; store the conclusion, not raw output.

Input Schema

NameRequiredDescriptionDefault
kindYes
refsNo
tagsNo
scopeNo
anchorNo
contentYes
projectNo
global_memoryNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It usefully discloses that this is a WRITE operation and adds the explicit-consent precondition, but it does not describe overwrite/duplicate behavior, persistence guarantees, failure modes, or other side effects an agent might need for a mutation tool.

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 front-loaded with the operation and precondition, then uses compact semicolon-separated parameter notes. It is dense but efficient, with no obvious filler; the opaque "§15" reference is the main minor structure issue.

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 an 8-parameter mutation tool with no annotations and 0% schema description coverage, the description covers the core intent, consent precondition, and several important parameters. However, it leaves multiple parameters undocumented and does not explain duplicate handling or lifecycle behavior, so it is only partially complete.

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 description coverage is 0%, so the description must explain parameters. It adds useful meaning for kind, scope, global_memory, and refs, but leaves tags, anchor, project, and content without semantic detail beyond the schema field names.

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 states a specific verb and resource: "WRITE. Store one memory." This clearly distinguishes the tool from read-oriented siblings such as search_memories and list_recent, though it does not explicitly name an alternative tool.

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 gives a strong precondition: only store when the user explicitly asked or confirmed a proposed fact, and never store silently. That provides clear when-to-use and when-not-to-use guidance, but it does not route the agent to sibling alternatives for adjacent tasks.

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