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vbcherepanov

total-agent-memory

session_end

Record final session state including summary, highlights, pitfalls, and next steps. Optionally auto-compress from transcript to preserve context for future sessions.

Instructions

End-of-session capture: summary + highlights + pitfalls + next_steps so the next session can resume cleanly. Set auto_compress=true to have the LLM generate the missing summary/next_steps/pitfalls from stored session artifacts (or from an optional transcript).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNogeneral
summaryNo
pitfallsNo
highlightsNo
next_stepsNo
session_idYes
transcriptNo
auto_compressNo
open_questionsNo

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Discloses the auto_compress behavior, explaining that setting it to true generates missing fields from stored artifacts or transcript. However, it does not mention side effects such as overwriting existing session data, and annotations provide no safety hints (all false), so the description carries more burden but still leaves some ambiguity.

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 succinct, consisting of two sentences with no redundancy. It front-loads the core purpose and then adds the key behavioral detail about auto_compress, maintaining efficiency.

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

Completeness3/5

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

Provides enough to understand the core action and the auto_compress feature, but lacks crucial context: it does not state whether any fields are required when auto_compress is false, nor how this tool fits relative to sibling session/memory tools. This could lead to incorrect usage.

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?

The description explicitly mentions several parameters (summary, highlights, pitfalls, next_steps, transcript, auto_compress) and explains auto_compress. However, it does not clarify the purpose or usage of required session_id, project, or open_questions. Given low schema coverage (0%), it partially compensates but leaves gaps.

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?

Clearly states it is an 'End-of-session capture' with specific fields (summary, highlights, pitfalls, next_steps), giving a clear verb and resource. It implies a specific usage context but does not explicitly distinguish from sibling tools like memory_save or session_init.

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 phrase 'End-of-session capture' and 'so the next session can resume cleanly' provide a temporal context, but the description does not explicitly mention when to use this over alternatives or when not to use it. It lacks direct guidance against using other memory tools.

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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