Skip to main content
Glama

agent_handshake

Declare your environment — model, client, languages, platform, and project goal — to receive optimal configuration. Unknown fields get sensible defaults.

Instructions

Personalized agent onboarding. Declare your environment and get optimal config.

Call this FIRST when connecting to MidOS. Pass as much info as you know. Unknown fields can be left empty -- you'll get sensible defaults.

Args: model: Your model ID (e.g. 'claude-opus-4-6', 'gemini-2.5-pro', 'opus') context_window: Your context window in tokens (e.g. 200000). 0 = auto-detect from model. client: Your CLI/IDE (e.g. 'claude-code', 'cursor', 'windsurf', 'cline') languages: Comma-separated languages (e.g. 'python,typescript') frameworks: Comma-separated frameworks (e.g. 'fastapi,react') platform: Your OS (e.g. 'windows', 'linux', 'macos') project_goal: What you're working on (e.g. 'manga engine with SVG rendering')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
context_windowNo
clientNo
languagesNo
frameworksNo
platformNo
project_goalNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It describes the tool as onboarding and returning config, but does not specify whether it is read-only, if it modifies state, or if it has side effects like registering the agent.

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?

Well-structured with a brief summary, a clear imperative to call first, and a bulleted list of arguments. Every sentence adds value without unnecessary verbosity.

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?

Covers the usage scenario well for an onboarding tool. The description does not detail the return value, but an output schema exists. Minor gap: it could hint at whether the configuration is saved or just returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description includes a detailed Args section with examples, units, and instructions for every parameter (e.g., '0 = auto-detect from model' for context_window). This fully compensates for the schema deficiency.

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?

Clearly states the tool's purpose: 'Personalized agent onboarding' to 'Declare your environment and get optimal config'. It also explicitly says 'Call this FIRST when connecting to MidOS', distinguishing it from any other tool that might be called later.

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?

Provides explicit guidance to call this first and to pass as much info as possible. Although it doesn't explicitly mention when not to use or alternatives, the context makes it clear that this is the initial setup call.

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/MidOSresearch/midos-mcp'

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