Skip to main content
Glama

retrieve_memory

Retrieve semantically similar memories from the current repository or across the organization to find relevant context for your query.

Instructions

Retrieve the top-k memories most similar to the query. If include_org=True, also queries sibling repositories in the same organization.

repo_path: optional absolute path to the target repository. When omitted, defaults to the server's configured project directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
include_orgNo
repo_pathNo
Behavior3/5

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

With no annotations provided, the description partially carries the burden. It discloses the retrieval behavior and the effect of 'include_org', but fails to mention potential limitations, authentication requirements, or whether the operation is read-only. The description is adequate but not comprehensive.

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 very concise, consisting of two sentences and a line for 'repo_path'. Every sentence provides essential information without fluff, and the key behavior 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 the absence of an output schema, the description does not explain return values or define what constitutes a 'memory'. It is adequate for a simple retrieval but lacks completeness for a tool with 4 parameters and many siblings.

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 schema description coverage is 0%, so the description must add meaning. It explains 'repo_path' in detail (optional, defaults to server directory), but provides no explanation for 'query', 'top_k', or 'include_org'. This partial coverage is mediocre.

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 action ('Retrieve the top-k memories'), the resource ('memories'), and key modifiers ('most similar to the query', 'include_org=True'). This effectively distinguishes it from sibling tools like 'semantic_search_code' or 'episodic_search' by focusing on 'memories'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lacks explicit guidance on when to use this tool versus alternatives. It mentions the 'include_org' option but does not provide criteria for when to use this tool over other search or retrieval tools in the sibling list.

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/ashlesh-t/cognirepo'

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