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Python
Hybrid

read_memory

Reads the full content and metadata of a specific memory entry by ID from the workspace Memory Vault.

Instructions

Reads the full content and metadata of a specific memory entry by ID from the workspace Memory Vault.

Args:
    memory_id: The ID of the memory entry to retrieve (e.g. 'mem_a1b2c3d4').
    workspace_dir: Workspace root directory. Empty = engine.default_workspace
           from the config, else the server's current directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
memory_idYes
workspace_dirNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.1.1
    • changedInput schema / properties / workspace_dir / default
      Previous value: -"."New value: +""
  2. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It conveys that this is a non-mutating retrieval of content plus metadata, but says nothing about failure behavior (e.g. unknown memory_id), permissions, or cross-workspace access. The output schema covers the return shape, so that omission is acceptable.

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-loaded one-sentence purpose followed by per-argument documentation. Slightly verbose in the workspace_dir fallback chain, but every detail there is operationally useful rather than filler.

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

Completeness4/5

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

Two parameters, both documented, one required; an output schema exists so return values need not be explained. The main remaining gap is the absence of any guidance on error/nonexistent-ID behavior, which for a no-annotation read tool would be the last thing worth adding.

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 description coverage is 0%, so the description must compensate - and it does. It documents both parameters, including an ID format example ('mem_a1b2c3d4') and the non-obvious fallback semantics of an empty workspace_dir (engine default from config, else server's current directory). That is meaningfully more than the bare schema.

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 and resource: reads the 'full content and metadata' of a memory entry, scoped 'by ID'. This implicitly distinguishes it from the sibling search_memory (query-based) and save_memory (write), though it never names those alternatives explicitly.

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?

Usage is implied by the 'by ID' framing - an agent infers this is the tool to call once it already holds a memory_id. However, there is no explicit statement of when to use this versus search_memory, and no prerequisites or conditions given.

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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