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Install Codegraph CLI

codegraph_setup_install
Idempotent

Installs the official Codegraph CLI on the target computer after the user explicitly agrees. Always set confirm=true only after that agreement. Prefer this over ad-hoc Shell install scripts. After success, register registry_hint into MCP Gateway when Manager tools exist (explore+impact only by default), then call codegraph_setup_init_project for the coding project. 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": {
      "confirm": "<confirm>"
    },
    "name": "codegraph_setup_install"
  }
}

Input Schema

NameRequiredDescriptionDefault
confirmYesMust be true only after the user explicitly agrees to install Codegraph on this computer.
device_idNoTarget computer device_id. Omit when only one computer is paired.
device_nameNoComputer name or ailinkany.com remark (e.g. home PC). Prefer this when the user names a computer.
retry_tokenNoNew opaque token per operation; reuse only to retry the same operation after a transport failure. No user content.
workflow_idNoOptional workflow id; pass together with ai_session_id.
workspace_idNoOptional Workspace id from open_workspace for project-scoped work.
ai_session_idNoOptional 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

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare non-read-only, idempotent, non-destructive, open-world behavior; the description adds the important consent gate, the post-install registration step, and the downstream init call, which are not derivable from annotations. It does not describe failure modes or that installation mutates the remote host beyond device targeting, but the rich annotations plus an output schema make that a minor gap.

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 critical consent rule is front-loaded, but the paragraph then drifts across post-install registration, intent matching, context inheritance, and trigger-keyword advice without clear ordering. The sentence "Select this tool from the user's intent when it is the best match" is tautological filler that adds nothing after the more concrete clarification about not needing to mention specific names.

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 consent-gated remote install with an output schema and full annotation coverage, the description supplies the key things an agent needs: the consent precondition, the preferred alternative, and the follow-up sequence. Only failure handling and what happens to a pre-existing installation are left unstated, which the annotations and output schema largely cover.

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 the schema already documents all seven parameters including confirm and the device targeting fields; the description adds only interpretive guidance about the destination being explicit or inherited from conversation context. The operational parameters (retry_token, workflow_id, workspace_id, ai_session_id) get no added narrative meaning, so the baseline 3 applies.

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 — installing the official Codegraph CLI on the target computer — and immediately scopes it to a consent-gated action. It also distinguishes itself from the generic shell_execute path ("Prefer this over ad-hoc Shell install scripts") and from its sibling codegraph_setup_init_project by ordering the two steps.

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

Usage Guidelines5/5

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

Gives explicit when-to-use conditions (after explicit user agreement, confirm=true only then), an explicit alternative to avoid (ad-hoc shell install scripts), and a prescribed follow-up sequence (register registry_hint via MCP Gateway when Manager tools exist, then call codegraph_setup_init_project). This is unusually complete routing guidance.

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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