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vbcherepanov

total-agent-memory

memory_extract_session

Extract pending session transcripts to save knowledge. List, retrieve, and complete sessions to capture and process prior work.

Instructions

Get pending session transcripts for knowledge extraction. Previous sessions are auto-captured on exit. Use action='list' to see pending, 'get' to read transcript, then save knowledge via memory_save, then 'complete' to mark as processed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chunkNoChunk number for large transcripts (0-based)
actionYeslist: show pending sessions. get: return transcript data. complete: mark as done.
session_idNoSession ID (required for 'get' and 'complete')

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

The description discloses that sessions are auto-captured on exit and that 'complete' marks them as processed, which are side effects. This is consistent with readOnlyHint=false. It doesn't mention any destructive actions, aligning with destructiveHint=false, but doesn't elaborate on state changes beyond marking processed.

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 concise sentences. The first states the purpose, the second gives the workflow. There is no redundancy or unnecessary detail, making it easy to parse and act on.

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?

For a tool with 3 parameters and no output schema, the description covers the primary workflow and parameter usage. It doesn't mention output format, error handling, or chunking details, but given the simplicity and the presence of schema descriptions, it is sufficiently complete for an agent to invoke correctly.

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?

The schema already covers parameter meanings (action enum, session_id required for get/complete, chunk for large transcripts). The description adds value by explaining the workflow order and how the parameters are used together, which goes beyond simple definitions. This is helpful, though not essential.

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 the tool's purpose: retrieving pending session transcripts for knowledge extraction, with a specific verb and resource. It also mentions automatic capture on exit, providing context. However, it does not explicitly differentiate from sibling tools like memory_get or memory_recall, so it's not a perfect 5.

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 description provides a clear workflow: use action='list' to see pending, 'get' to read, then save via memory_save, and 'complete' to mark processed. It mentions a subsequent step (memory_save) which gives usage context. It doesn't explicitly state when not to use this tool or compare it to alternatives, but the workflow is helpful.

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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