decarbonization_roadmap

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

With no annotations, the description carries full burden. It honestly discloses that abatement costs are modeled and indicative, that offsets are flagged as compensation not reduction, and that targets beyond reduction levers are labeled. It also mentions pricing model (PREMIUM: pay per call). No contradictions with annotations.

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?

The description is relatively long but well-structured, starting with the main purpose then detailing levers and outputs. While each sentence adds value, it could be slightly more concise; however, it remains clear and informative.

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?

Given the tool's complexity and lack of output schema, the description covers inputs, levers, return values (ordered roadmap with tonnes abated, cost, etc.), limitations, and pricing. It is thorough and leaves minimal gaps for an agent to understand usage.

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?

Although schema coverage is 100%, the description adds meaning beyond the schema by explaining the role of parameters (e.g., origin_port/dest_port for lane-based baseline, baseline_co2e_tonnes for network footprint, allowed_levers for restriction, cost_band for sensitivity). It provides context that the schema alone does not.

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?

The description clearly states the tool's purpose: to create a decarbonization roadmap for a transport network. It uses specific verbs like 'cut the carbon' and 'walks the abatement levers', and lists the exact levers involved. It distinguishes from sibling tools like carbon_footprint (which only measures) and optimize_network (which is broader).

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?

The description provides explicit conditions for use: 'Give a lane (or an annual network footprint in tonnes CO2e) and a reduction TARGET %'. It explains what the tool does with the inputs. However, it does not explicitly state when not to use this tool or mention alternatives, though the context implies it.

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