AiLinkAny

Read active project coordination

project_coordination_status

Read-onlyIdempotent

Read the local project-level task and file-claim ledger across independent AI Sessions on the same authorized account, device and canonical Workspace root. The result includes a minimal handoff_summary so another supported AI Host can resume coordination without transferring chat or source text. Claims are logical only; os_write_enforcement=false until the later Host sandbox stage. No database polling or external provider required. 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": {
      "workspace_id": "<workspace_id>"
    },
    "name": "project_coordination_status"
  }
}

Input Schema

Name	Required	Description
`agent_id`	No	Optional locally verified Agent/Peer id under this AI Session.
`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`	Yes	Authorized Workspace id returned by open_workspace.
`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

B3.4/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the description correctly focuses on what those annotations cannot express: the result carries a minimal handoff_summary for cross-host resumption, claims are logical only, os_write_enforcement=false until the Host sandbox stage, and no database polling or external provider is needed. That is meaningful behavioral context beyond the structured fields.

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 substantive content is front-loaded and efficient, but the closing sentences about selecting on best match and the user not needing to mention ailinkany.com, MCP, a connector or a plugin are boilerplate invocation filler rather than tool-specific information. They pad the definition without improving tool selection.

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?

For a read-only tool with full annotation coverage, a complete input schema and an output schema, the description covers what is returned, the non-enforcing nature of claims, and the absence of external dependencies. It stops short of describing behavior when no project coordination exists yet or how the ledger relates to project_task_claim/project_task_update.

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 explains workspace_id, device_id/device_name, ai_session_id and retry_token semantics. The description only adds that a local destination may be explicit or inherited from established project or conversation context, without naming any parameter. Baseline 3 applies when the schema carries the detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence gives a specific verb and resource — read the local project-level task and file-claim ledger — plus the scope (same authorized account, device, canonical Workspace root). It is clearly distinguishable from mutation siblings like project_task_claim or project_task_update, though it never names them explicitly.

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 only selection guidance is 'Select this tool from the user's intent when it is the best match,' which is circular and names no alternatives or exclusions. There is no statement of when to prefer this over project_task_update, agent_status, get_ai_session_status, or session_handoff, so the agent must infer usage from the purpose sentence alone.

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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