Skip to main content
Glama
parth0072
by parth0072

remember

Save durable facts, preferences, decisions, or tasks to a shared local memory, enabling AI clients to retain context across sessions and models.

Instructions

Save a durable fact, preference, decision or task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNofact
tagsNo
textYesone self-contained statement
sourceNowhich AI/app is saving
projectNoglobal
importanceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing beyond 'durable'. It does not say whether writes are deduplicated, append-only, scoped to a project, or how conflicts are resolved — all material for a persistence 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?

One short, front-loaded sentence with no filler; the verb leads and the accepted content types follow. It is efficient, though arguably too terse to be informative given the parameter surface.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 6-parameter persistence tool with no annotations and no output schema, the definition leaves too much unspecified: retention, project scoping, importance scale meaning, and duplicate handling are all absent. Nothing an agent needs to call it correctly is covered.

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

Parameters2/5

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

Schema description coverage is only 33% across 6 parameters, so the description would need to compensate. It enumerates four of the five kind enum values (omitting 'note', which is slightly misleading) but says nothing about importance, tags, project, or source semantics.

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?

States a specific verb (Save) and the resource types it accepts (durable fact, preference, decision, task), which reads as a write-side memory tool. It does not name or contrast with siblings like recall or save_handoff, but an agent can still tell it apart by the persist-a-statement action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this over save_handoff, export_markdown, or recall, and no mention of prerequisites or when-not-to-use. The only implied usage is that the content must be a durable statement, which the agent must infer.

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