Skip to main content
Glama

Read Handoff

read_handoff
Read-only

Read shared .ai-bridge planning files to retrieve coordination context between ChatGPT and your coding agent for continued work.

Instructions

Read the shared .ai-bridge planning files used for ChatGPT-to-agent coordination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_idNoWorkspace id from open_workspace. Omit to use default workspace.
Behavior4/5

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

Annotations (readOnlyHint, destructiveHint) already disclose that this is a safe read operation. The description adds context about the file type and coordination purpose, which is useful. However, it doesn't disclose the return format or error behavior, but with annotations covering the safety profile, this is acceptable.

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?

A single, clear sentence that front-loads the key action and resource. There is no redundant wording or filler, making it concise and easily parseable.

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?

Since there is no output schema, the description should clarify what the agent receives when the tool succeeds. It doesn't mention return format, possible errors, or what happens if files are missing. The parameter is optional and uses a default, which is covered in the schema, but the read operation's output is left ambiguous. This is a moderate gap for a tool with no output schema.

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 covers 100% of parameters with a description ('Workspace id from open_workspace. Omit to use default workspace.'), so the tool description adds no additional semantic weight. Baseline 3 is appropriate because the schema already documents the parameter well.

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 uses a specific verb ('read') and names a distinct resource ('.ai-bridge planning files'), while adding the purpose ('ChatGPT-to-agent coordination'). This clearly differentiates it from the generic 'read' sibling tool by specifying the exact file type and scope.

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 conveys when to use the tool—when reading shared coordination files—but does not explicitly mention alternatives or when not to use it. The context is clear enough for an agent to infer its intended use, though it lacks explicit exclusions.

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/sedatustunova/S3dat-Relay'

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