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memorygraph

memorygraph

by xbrxr03
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Record observation

record
Idempotent

Record raw observations without inference, supporting procedural memory with task metadata and outcomes.

Instructions

Store one user-approved raw observation without inferring claims. Set kind to attempt to record procedural memory; content is the strategy and metadata must include task_key and outcome, with optional failure, applicability, and environment.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "bank": "<bank>",
      "content": "<content>",
      "source_key": "<source_key>"
    },
    "name": "record"
  }
}

Input Schema

NameRequiredDescriptionDefault
bankYesBank slug or UUID.
kindNo
contentYes
actor_idNo
metadataNo
workspaceNoOptional workspace label stored on observations.
actor_typeNo
source_keyYes
observed_atNo
sensitivityNo
trust_classNo
effective_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds context about user approval and non-inference of claims, which are beyond the annotations. But it doesn't disclose other behaviors like error handling, rate limits, or side effects beyond the basic write operation, so it adds some value but not a lot.

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?

The description is two sentences with zero fluff. It front-loads the core purpose, then gives a focused, actionable instruction for the most complex parameter combination. Every word earns its place, and the layout makes it easy to scan.

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 tool with 12 parameters, nested objects, and no output schema, the description is insufficient. It only addresses the 'attempt' kind and does not cover other potential uses or explain most parameters. There is no mention of return values, error cases, or examples. While annotations cover idempotency and destruction, the description leaves too much to inference for a complex tool.

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 only 17%, so the description carries considerable burden. It clarifies kind, content, and metadata specifically for the 'attempt' case, which is valuable. However, it leaves the majority of the 12 parameters (e.g., actor_id, actor_type, sensitivity, trust_class) unexplained, and provides no general semantics for other kinds. It partially compensates for the low coverage but not fully.

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 clearly states a specific verb ('Store') and resource ('raw observation'), with a qualifier ('user-approved') and a constraint ('without inferring claims'). It is unambiguous, though it doesn't explicitly distinguish from sibling tools like 'explain' or 'recall', which prevents a perfect score.

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

Usage Guidelines3/5

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

The description provides explicit guidance for a specific scenario (setting kind to 'attempt') and outlines required metadata fields. However, it lacks any guidance on when this tool should be used compared to siblings, no exclusions or alternatives are mentioned, so it's partially helpful but not comprehensive.

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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