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linancn

TianGong-LCA-MCP Server

by linancn

LCA_Calculation_Guidance_Tool

Provides step-by-step workflows for conducting Life Cycle Assessment calculations to obtain Life Cycle Impact Assessment results.

Instructions

Get the workflow, which should be followed for Life Cycle Assessment (LCA) Calculations to Obtain Life Cycle Impact Assessment (LCIA) Results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions getting a workflow, but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication, what format the workflow is in (e.g., text, structured data), or any rate limits. This leaves significant gaps in understanding how the tool behaves.

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?

The description is a single, clear sentence that efficiently states the tool's purpose. It's front-loaded and avoids unnecessary words, though it could be slightly more specific to improve clarity without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of LCA calculations and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the workflow output looks like (e.g., steps, format), how it integrates with other tools, or any dependencies, leaving the agent with insufficient context for effective use.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, earning a baseline score of 4 as it doesn't need to compensate for any schema gaps.

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

Purpose3/5

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

The description states the tool provides a workflow for LCA calculations to obtain LCIA results, which is a clear purpose. However, it's somewhat vague about what exactly the workflow entails (e.g., steps, format) and doesn't explicitly differentiate from sibling tools like OpenLCA_Impact_Assessment_Tool, which might also relate to LCIA results.

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 description implies usage for LCA calculations to get LCIA results, but it doesn't specify when to use this tool versus alternatives like OpenLCA_Impact_Assessment_Tool or other siblings. No explicit guidance on prerequisites, exclusions, or context is provided.

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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