Skip to main content
Glama

summarize_session

Groups session memories into decisions, insights, action items, and context to provide a structured review of key takeaways before ending a session.

Instructions

Summarize a session's key decisions, insights, and action items.

Groups session memories by semantic category to extract structured knowledge:

  • Decisions: Choices made and their rationale

  • Insights: Lessons learned, antipatterns, landmines, constraints

  • Action Items: TODOs, bugs, tasks to complete

  • Context: Background info, conventions, preferences, architecture

Use this before end_session() to review what was captured, or anytime to get a structured view of a conversation's key takeaways.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesSession ID to summarize

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description must cover behavioral traits. It describes the grouping logic and output categories (decisions, insights, action items, context), implying a read-only review operation. However, it does not mention error handling, permissions, or side effects, leaving some gaps.

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 paragraphs: first states purpose, second lists categories and usage guidance. It is front-loaded, each sentence adds value, and there is no redundant or verbose content.

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?

Given the tool has a single parameter and an output schema (context signal), the description adequately explains what the tool does and when to use it. It covers the output categories and use cases. Missing details about error conditions (e.g., session not found) but overall complete for its simplicity.

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 coverage is 100% (one parameter 'session_id' with clear description). The tool description adds context about what the summary includes but does not add further semantics about the parameter itself. With high schema coverage, baseline 3 is appropriate.

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?

The description clearly states 'Summarize a session's key decisions, insights, and action items' and specifies grouping by semantic categories, distinguishing it from siblings like 'get_session' or 'remember'. It also mentions a use case relative to 'end_session()'.

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?

Explicitly says 'Use this before end_session() to review what was captured, or anytime to get a structured view', providing clear context for when to use the tool. Does not explicitly mention when not to use or list alternatives, but the guidance is helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/michael-denyer/memory-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server