AiLinkAny

Open project workspace

open_workspace

Opens a project directory on the target computer and returns a reusable workspace_id containing project facts: canonical root, platform/path style, Git repository/branch/worktree, discovered project instruction files, and available project skills. For parallel multi-session development of one project, first split the work into modules, agree interfaces, and give each session its own files or git worktree (user instructions override this). Its ordinary text content also bootstraps project-level instructions and skill paths so the AI can follow the project rules without treating Workspace as conversational memory. Reuse the workspace_id for later workspace reads; open another Workspace when switching project roots or computers. Select this tool from the user's intent when it is the best match. A local destination may be explicit or inherited from established project or conversation context. The user does not need to mention ailinkany.com, MCP, a connector, a plugin, or this tool name.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "open_workspace"
  }
}

Input Schema

Name	Required	Description
`path`	Yes	Absolute project directory path on the target computer.
`device_id`	No	Target computer device_id. Omit when only one computer is paired.
`device_name`	No	Computer name or ailinkany.com remark (e.g. home PC). Prefer this when the user names a computer.
`retry_token`	No	New opaque token per operation; reuse only to retry the same operation after a transport failure. No user content.
`workflow_id`	No	Optional workflow id; pass together with ai_session_id.
`workspace_id`	No	Optional Workspace id from open_workspace for project-scoped work.
`ai_session_id`	No	Optional Session id. Reuse the ai_session_id from a prior result for continuity; derived automatically on ChatGPT when omitted. Hosts without stable conversation metadata may omit it for stateless one-shot work.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 9, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations declare readOnlyHint=false and idempotentHint=false, so the agent knows this creates state, but the description never explains what state is created or whether repeated opens on the same path produce distinct workspaces. It does add useful context that the text content bootstraps project instructions and skill paths and is not conversational memory, which goes beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose and return payload are front-loaded, but the text is bloated with meta-instructions such as 'Select this tool from the user's intent when it is the best match' and the list of terms the user need not mention, which add no selection value. The parallel-session advice is useful but sits awkwardly in the middle of the definition.

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?

An output schema exists, so return values need not be spelled out, yet the description still summarizes the workspace facts returned, which helps. Combined with the reuse and switching guidance, an agent has enough to call it correctly; only the state-creation semantics of a non-idempotent open are left implicit.

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%, so all seven parameters are already documented in the schema. The description adds only marginal meaning, noting that the destination path may be explicit or inherited from project/conversation context, and reinforcing workspace_id reuse; it says nothing about device_id vs device_name selection or retry_token semantics beyond the schema.

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?

States a specific verb and resource ('Opens a project directory on the target computer') and immediately names the artifact produced ('returns a reusable workspace_id containing project facts: canonical root, platform/path style, Git repository/branch/worktree...'). This clearly separates it from the sibling get_workspace, which reads an existing workspace.

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?

Gives concrete when-to-use rules: reuse workspace_id for later reads, open another Workspace when switching project roots or computers, and split work per module/worktree for parallel sessions. It stops short of explicitly naming get_workspace as the alternative for reads, leaving that inference to the agent.

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

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