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Filipe-Soares-de-Almeida

MemAI

by Filipe-Soares-de-Almeida
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Python
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get_memory

Read-onlyIdempotent

Retrieve one MemAI memory by UID to inspect its fields and linked-item counts; use offsets to page long edit history or body content.

Instructions

Fetch one memory: its fields, and counts of what is linked to it.

next names the call that pages each part: get_relations() for relations and diagrams, get_diagram() for a diagram's graph, task_read() for a task's items, notes and comments, edits_offset for the edit history and content_offset for a body too long for one response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYesthe memory.
edits_offsetNofrom -1 to a page start, reads the edit history instead of the record, bodies cut to 4000 characters.
content_offsetNofrom -1 to a character offset, reads that stretch of the body instead of the record.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.16.1
    • addedInput schema / properties / content_offset
      Added value: +{
+  "default": -1,
+  "description": "from -1 to a character offset, reads that stretch of the body instead of the record.",
+  "type": "integer"
+}
    • addedInput schema / properties / edits_offset
      Added value: +{
+  "default": -1,
+  "description": "from -1 to a page start, reads the edit history instead of the record, bodies cut to 4000 characters.",
+  "type": "integer"
+}
    • addedInput schema / properties / uid / description
      Added value: +"the memory."
    • removedInput schema / properties / uid / title
      Removed value: -"Uid"
    • removedInput schema / title
      Removed value: -"get_memoryArguments"
  2. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds real behavioral detail: that linked data is only counted, that parts are paged via 'next', and that bodies can exceed one response. It stops short of describing error behavior when a uid is missing.

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 with the core purpose in one sentence, then a compact routing sentence. The second sentence is dense with call names but every clause carries usable information; no 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?

With no output schema, the description must carry return-value semantics, and it does: fields, counts, and how each paginated part is retrieved. The only gap is that the shape of 'fields' and the count keys themselves are left unspecified.

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 the baseline is 3, but the description adds genuine meaning: edits_offset switches to edit history with bodies cut to 4000 characters, and content_offset reads a character stretch of the body. This clarifies the mode-switching behavior of the two optional params beyond the schema's own wording.

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?

States a specific verb and resource ('Fetch one memory') plus the scope of what is returned ('its fields, and counts of what is linked to it'), which cleanly separates it from sibling list/search tools like recall, search, and list_recent.

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?

The second sentence explicitly routes the agent to the correct follow-up calls for each paginated part (get_relations() for relations/diagrams, get_diagram() for a graph, task_read() for task items). It does not, however, say when to prefer get_memory over siblings such as search or recall when the uid is unknown.

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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