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by Patdolitse
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

save_project_snapshot

Destructive

Write or update a project's knowledge snapshot: save its tech stack, known issues, and notes as structured JSON so context persists across sessions and tools.

Instructions

写入或更新项目的知识快照（写操作，不是读取）。 / Write or update a project's knowledge snapshot; this is a write operation, not a read.

用途：保存或更新当前项目的技术栈、已知问题、注释等信息。
Purpose: Call to save or update a project's tech stack, known issues, notes, and related metadata.

注意：读取项目快照用 get_project_context，不是本工具。
Note: Use get_project_context to read a project snapshot; this tool writes one.

Args:
    project_folder: 项目文件夹路径。 / Project folder path.
    data_json: JSON 字符串，支持字段 title、tech_stack、known_issues、notes。 / JSON string supporting fields: title, tech_stack, known_issues, and notes.

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_folder": "<project_folder>",
      "data_json": "<data_json>"
    },
    "name": "save_project_snapshot"
  }
}

Input Schema

NameRequiredDescriptionDefault
data_jsonYes
project_folderYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.29.1

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=true, and idempotentHint=false. The description confirms the tool mutates data and lists the fields it writes, but it does not add beyond-annotation specifics such as whether an existing snapshot is replaced vs merged, or the exact data-loss implications of the destructive write.

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 purpose is front-loaded and the Args section is useful, but the entire content is duplicated in Chinese and English. That duplication inflates length without adding information, so it is only moderately concise.

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 two-parameter write tool with an output schema and rich annotations, the description supplies the purpose, both parameter meanings, the supported data fields, and the read alternative. A minor gap remains around overwrite vs merge semantics, which is relevant for a destructive write.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does document both required parameters: project_folder as the project folder path and data_json as a JSON string supporting title, tech_stack, known_issues, and notes. It lacks format examples or constraints, keeping it below a top score.

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 states a specific verb and resource: write/update a project's knowledge snapshot. It explicitly says this is a write operation, not a read, and names get_project_context as the read counterpart, making it easy to distinguish from siblings.

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?

It clearly identifies when to use the tool: saving or updating tech stack, known issues, notes, and related metadata. It also explicitly names when not to use it and which alternative to use instead: get_project_context for reading.

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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