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jeremiahsay

GreenCalculus

resolve_factor

Resolve a plain-language emission factor request into ranked key candidates, with country-specific matching.

Instructions

Find the best emission-factor key(s) for a plain-language description — the hardest step is picking the right key out of ~16,000. Returns ranked candidates; feed the chosen key to a calculate_* tool or lookup_factor. Prefer this over guessing a key. PUT THE COUNTRY IN THE DESCRIPTION. Geography is read from the description text itself, not from a separate field — "diesel per litre" and "diesel per litre France" resolve differently, and omitting the country will quietly return a factor from somewhere else marked "geo_match":"proxy". ACT ON THE LABEL. Every candidate carries label: "accept" or "review", plus "why". "accept" means confidence >= 0.85 and no demotion applied — right about nine times in ten. "review" means the answer may be usable but something is off (low confidence, only one term matched, a proxy country, or a gate demoted it); confirm it before adopting the number rather than using it silently. Roughly half of CORRECT answers are also flagged "review" — that is the intended trade, so treat "review" as "check this", not "discard this". A MISS MAY EXPLAIN ITSELF. When nothing matches, or the only matches are from the wrong country, the response may carry an "absence" object saying WHY. classification "structural" means no publisher issues this anywhere — STOP, do not retry with reworded queries and do not substitute a different country without saying so. "not_yet_sourced" means a publisher exists and we have not ingested it (the publisher is named). "refused" means we found the data and declined it, with the reason. "coupled" means this reads empty only because a related family is empty. Use explain_absence to ask the same question directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional, default 5.
sectionNoOptional section filter, e.g. "fuels", "grid", "freight".
descriptionYesWhat you need a factor for, INCLUDING the country if it matters, e.g. "UK grid electricity", "diesel per litre France", "hotel stay Japan". Geography is parsed from this string.
Behavior5/5

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

Extensively explains return labels, absence types, geography handling, and proxy behavior.

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

Conciseness2/5

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

Description is very verbose and repetitive, could be condensed.

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

Completeness5/5

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

Covers all key aspects: output candidates, labels, absence handling, and next steps.

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 already describes parameters; tool description adds some clarification but not much beyond schema.

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?

Clearly states it finds the best emission-factor key for a plain-language description, distinguishes from lookup/calculate tools.

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 guidance on when to use (prefer over guessing) and how to include country, but could be more explicit vs other search tools.

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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