Skip to main content
Glama

memory_archive

Archive session findings into learnings for PM review. Specify a session ID to convert its L2 findings into L1 learnings.

Instructions

将指定 session 的 L2 findings 归档为 L1 learnings。PM 审查后调用。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keysNo指定要归档的键名,省略则归档该 session 全部 findings。
projectNo目标项目的绝对路径(如 D:/code/project-a)。省略则使用当前项目。
session_idYes要归档的源 session ID。
target_namespaceNo目标命名空间,默认 project/learnings。project/learnings
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses the main action (archival from L2 to L1) but lacks details on side effects (e.g., whether L2 findings are deleted), permissions needed, or idempotency. Adequate but could be more transparent.

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 a single short sentence that conveys the core purpose efficiently. No wasted words, and it is front-loaded.

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?

Given no output schema and no annotations, the description is minimal. It does not explain what L2 findings vs L1 learnings entail or the exact archival semantics. Adequate for a simple tool but lacks depth for a complex domain.

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 description coverage is 100%, so the schema already describes all parameters. The description adds no extra meaning beyond the schema, so a baseline of 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 the tool archives L2 findings from a session into L1 learnings, specifying the direction (L2 to L1) and a precondition (PM review). This distinguishes it from generic memory operations like memory_set or memory_delete.

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 includes a usage condition ('PM 审查后调用' meaning 'call after PM review'), providing clear context. It does not explicitly mention when not to use or alternatives, but the context is sufficient.

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/FirenzeClaw/kimi-session-orchestrator'

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