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xuanshang-canvas

xuanshang-canvas

by pencil102411-cell
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_graph_summary

Read-onlyIdempotent

Retrieve a project's canvas summary of video nodes, ordered input assets, task status, generated-video availability, and certification node names and IDs for inspecting or referencing project state.

Instructions

项目节点摘要：每个视频节点的名字、参数、按顺序列出的接入素材（图片1、视频1……）、最近任务状态、 是否已有生成好的视频（可以当参考）；以及认证图片节点、认证视频节点的名字和 ID。

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": {
      "project": "<project>"
    },
    "name": "get_graph_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectYes项目名称或项目 ID（用 list_projects 查）

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare the full safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the safety burden is lifted. The description adds useful scope detail — it aggregates across all video nodes plus certified image/video nodes and surfaces task status and existing outputs — but since an output schema is present, much of this restates return contents rather than adding new behavioral context.

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

Conciseness4/5

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

A single front-loaded sentence that opens with the summary subject and then enumerates contents. It is a long run-on list, but every clause carries information and there is no filler.

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?

With an output schema documenting the return shape and annotations covering the safety profile, the description only needs to convey scope and content, which it does. The one gap is the absence of any routing guidance among the many sibling status/listing tools.

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?

Only one parameter (project), and the schema already documents it at 100% coverage, including the pointer to list_projects. The description adds no format or syntax detail beyond the schema, so the baseline 3 applies.

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 description names the resource (项目节点摘要) and enumerates the concrete contents it returns: per-video-node name, parameters, ordered input materials, latest task status, whether a generated video exists, plus certified image/video node names and IDs. This is specific and distinguishing in substance, though it never explicitly contrasts itself with look-alike siblings such as canvas_status or get_task.

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?

There is no statement of when to call this tool versus alternatives — notably canvas_status, which appears to be a closely related status-listing sibling. The description describes what comes back but gives no selection criteria, prerequisites, or exclusions, leaving usage entirely to inference.

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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