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

Annotations already cover read-only/idempotent/non-destructive/closed-world, and the description adds what they cannot: data provenance (A-grade, European Commission official PDF), the validity window of the values, and the regulatory basis for the successor period. That vintage/provenance disclosure materially reduces the risk of an agent presenting stale factors as current.

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

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

Front-loaded with the resource and query axes, then provenance, then the critical exclusion, in five tight sentences. The specific regulation numbers ((EU) 2025/2621, (EU) 2026/1740) are verbose but guard against a real misuse, so they earn their place; a small trim would still help.

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

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

With a full output schema and 100% parameter coverage, the description needs only to set scope and caveats, which it does. The one remaining gap is relational: it never says how this factor lookup feeds siblings like calculate_cbam_cost, leaving the pipeline to the agent's inference.

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

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

Schema description coverage is 100%, so limit, cn_code, keyword, language, response_format and product_category are each already documented with examples and enums. The description only restates three of the query axes without adding syntax or precedence rules, so the baseline of 3 applies.

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

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

States a specific resource (CBAM default emission factors), the query axes (product category, CN code, keyword), and the exact return values (direct/indirect/total embedded emissions in tCO2e/t). This clearly differentiates it from siblings like calculate_cbam_cost or query_activity_guidelines, which are computation/guideline tools rather than factor lookups.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit scope boundaries: transitional period only (2023-10-01 to 2025-12-31), definitive period governed by other regulations, and 'Carbon black is NOT in CBAM scope' as a hard exclusion. It stops short of naming which sibling to use for cost calculations, but the when-not conditions are unusually concrete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.