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by com.greencalculus

lookup_factor

Look up a single greenhouse-gas emission factor by its canonical key. Returns the value plus an audit envelope: provenance (publisher, exact source cell, retrieval date, LICENCE and whether it may be redistributed, with the attribution the licence requires) and verification (whether the per-gas components sum to the headline, the GWP set, and the source note stating what the publisher did NOT provide). If the key does not exist you get candidate keys back rather than a dead end. Use search_factors first if you do not know the key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesCanonical factor key, e.g. "grid.gbr.electricity.location_based".

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It details the return envelope including provenance (publisher, cell, retrieval date, licence, redistribution, attribution) and verification (GWP set, source note), and even mentions what the publisher did not provide. This is unusually transparent.

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 a single, compact paragraph that front-loads the primary purpose, then details the return envelope and missing-key behavior. Every sentence adds value, and there is no redundancy or filler.

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?

Given there is no output schema, the description thoroughly explains what the tool returns, including the audit envelope fields and verification details, and what happens on a missing key. It covers all necessary behavioral aspects for a lookup tool with one parameter, making it complete.

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 description coverage is 100% and includes an example key, so the baseline is 3. The tool description adds no new parameter semantics beyond repeating 'canonical key,' which is already in the schema. The example in the schema is sufficient; the description offers no additional clarification.

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 looks up a single emission factor by canonical key, and explicitly distinguishes it from search_factors by noting that search_factors should be used when the key is unknown. The verb 'look up' and resource 'greenhouse-gas emission factor' are specific and unambiguous.

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?

The description explicitly says 'Use search_factors first if you do not know the key,' providing clear guidance on when to use this tool versus the alternative. It also explains the behavior when the key does not exist (candidate keys returned), giving users context on error handling.

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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct role: search, lookup single, lookup batch, resolution, absence explanation, and separate calculation methods for distinct scopes. Even the discovery tools can be told apart by whether the input is a key, text, natural language, or a purpose. Domain calculators are cleanly separated by type of activity, so an agent should not confuse them.

Naming Consistency5/5

All tools follow a consistent verb_nonn pattern: calculate_*, lookup_factor(s), search_factors, resolve_factor, explain_absence. The naming clearly signals both action and object, and even the singular/plur lookup distinction matches the batch versus single-key semantic.

Tool Count5/5

Twelve tools is well-sopened for a broad emissons-factor API: six calculators, four discovery/lookup/resolution tools, one batch lookup, and one edge-case explainer. Each tool appears to serve a necessary purpose rather than adding redundant surface area.

Completeness5/5

The set covers the full workflow: discover factors, resolve amiguous plain-language queries, look them up individually or in batch, perform domain-relevant calculations, and even explain why a factor is absent. The main GHG scopes are covered by dedicated calculators while the generic calculate_activity fills gaps for any other factor data.

Resources