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chang0911

丝路E投财务引擎 MCP 适配层

by chang0911

permitted_cost_excel

Converts pricing data JSON into a full-formula Excel model for permitted cost plus reasonable return pricing, covering assets, costs, revenue, and sensitivity. Returns a file link or base64.

Instructions

准许成本加合理收益定价:定价数据JSON → 全公式Excel(主表+固定资产+无形资产+有效资产+运营维护费+准许收益+趋势/敏感性,补贴模式含对外收入+政府补贴定价)。返回 file_base64(默认返回72h下载短链,return_mode="base64" 可回退)。数据收集五步与schema先看 get_skill_instructions(skill=permitted_cost)。前置:需先调 get_protocol_instructions。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes定价数据JSON:project(对象)+fixed_assets(数组)+intangible_assets(数组)+years(非空数组,含运行维护费与wacc)+revenues(可选,补贴模式)
file_nameNo成品文件名(.xlsx,遵循总则命名规范)
return_modeNo成品交付方式:base64(默认,兼容);url 推荐——返回72h下载短链(file.url),防大文件撑爆上下文,外部客户端建议默认 url

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses the default return (72h download short link) and the base64 fallback, which is useful. However it omits whether the operation is read-only/side-effect-free, permission requirements, and expected output characteristics beyond format.

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?

Information is front-loaded with the core purpose, but the sentence is dense and mixes purpose, output sheets, delivery modes, and prerequisites in one block. It is reasonably compact but not as structurally clean as it could be.

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?

Given the complex nested data schema and generated output, the description covers what the tool produces, delivery modes, and prerequisite tool calls. It is fairly complete, though it doesn't explain the division of labor with sibling Excel generators.

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 three parameters in detail. The description repeats the return_mode behavior and file naming conventions but adds little syntax or format meaning beyond what the schema provides.

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?

States a specific verb and resource (pricing data JSON → full-formula Excel workbook) and even enumerates the sheets produced. This is clearly distinguishable from siblings like estimate_excel or fast_calc_excel, though the description does not explicitly contrast with them.

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 prerequisites (call get_protocol_instructions first; see get_skill_instructions for the five-step data collection) and states the default vs. recommended delivery mode. It does not name an alternative sibling for the same task, but the prerequisite routing is concrete.

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