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jeremiahsay

GreenCalculus

calculate_spend

Calculate spend-based Scope 3 emissions by applying EEIO economic-intensity factors to your spend data. Use the matching sector factor and keep spend in the factor's currency for accurate results.

Instructions

Spend-based (EEIO) Scope 3 screening: emissions = spend × economic-intensity factor. Spend must be in the factor's own currency/year (no FX). Find sector factors via search_factors (section "spend_based"), e.g. spend_based.us.naics6.541511.custom_computer_programming_services.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
spendYes{ "value": <number>, "currency": "USD|GBP|EUR|SGD" }.
factor_keyYesSpend-based (EEIO) sector factor key.
Behavior3/5

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

No annotations are provided, so the description carries the burden. It mentions the input constraint (currency/year) but does not explicitly state whether the tool has side effects or read-only status. As a calculation, it's likely safe, but this is not confirmed.

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

Conciseness5/5

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

The description is concise, two sentences that pack the formula, the constraint, and a reference to search_factors. No unnecessary details, well-structured for quick comprehension.

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 there is no output schema, the description adequately explains the calculation context, including the EEIO methodology and how to obtain factor keys. The output (emissions) is implied by the formula, so it's sufficient.

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 schema provides basic descriptions, but the tool description adds significant meaning by explaining the spend format requirement and giving an example factor key. This enriches the understanding of both parameters.

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 clearly states the tool's purpose: calculating emissions using spend and economic-intensity factor, with the formula explicitly provided. This distinguishes it from sibling tools like calculate_activity or calculate_embodied.

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?

It explains the spend-based approach, emphasizes the currency/year constraint, and directs users to search_factors for finding factor keys. While it doesn't explicitly contrast with alternatives, the specific method and constraints make usage clear enough.

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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