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calculate_embodied

Whole-life embodied carbon for materials, per EN 15978. Give a material key + quantity (+ optional boundary A1-A3 / A1-A4 / A1-A5 / A1-C); it assembles the declared lifecycle modules (A1-A3, B, C1-C4, D) into stages, totals the boundary, reports module D separately, and flags any missing stage as not-assessed (never zero). Find material keys via search_factors (section "materials").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
materialsYesEach: { material_key, quantity:{value,unit e.g. m3/kg/tonne/m2}, boundary? }.

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: it assembles lifecycle modules (A1-A3, B, C1-C4, D) into stages, totals the boundary, reports module D separately, and flags missing stages as not-assessed (never zero). This goes beyond basic input/output and sets accurate expectations.

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 dense but every sentence earns its place: purpose, usage, behavior, and key lookup are all covered in three sentences. It is front-loaded with the core function and avoids fluff.

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?

For a complex calculation tool with no output schema and minimal annotations, the description covers purpose, input structure, boundary options, calculation behavior, and how to find valid keys. It is sufficiently self-contained for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% coverage but is minimal; the description adds significant meaning by specifying the accepted boundary values (A1-A3, A1-A4, A1-A5, A1-C) and giving example units for quantity. This helps the agent construct correct inputs.

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 calculates whole-life embodied carbon for materials per EN 15978, using a specific verb and resource. It distinguishes from sibling calculation tools (electricity, freight, etc.) and lookup tools via its material focus and reference to search_factors for keys.

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?

The description provides clear usage context: give a material key and quantity, optionally specify a boundary range, and find keys via search_factors. It does not explicitly state when not to use this tool compared to alternatives, but the material focus and boundaries make the intended use clear.

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.

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