Estimate AI environmental impact

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

With no annotations provided, the description carries full burden for behavioral traits. It discloses the methodology (EcoLogits) but does not explicitly state read-only nature, side effects, or limitations. The word 'estimate' implies computation without mutation, which is helpful but not fully transparent.

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 two sentences long, front-loading the output and input in the first sentence and methodology in the second. Every sentence is substantive with no waste.

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 no output schema, the description mentions the key output metrics (kWh, miles, water, CO2e), which is important context. However, it does not specify the return format, structure, or error handling. For a tool with 5 parameters, it is fairly complete but leaves minor gaps.

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 80%, so baseline is 3. The description adds minimal semantic value beyond the schema, only mentioning 'token counts' generally. It does not elaborate on model, scenario, or zone parameters, which are already described in the schema.

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 estimates environmental impact (energy kWh, miles, water, CO2e) for a single AI request given token counts. It specifies the methodology (EcoLogits). However, it does not explicitly differentiate from siblings like analyze_efficiency or efficiency_score, which may have overlapping purposes.

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 implies usage for estimating impact of a single request based on token counts, but does not provide explicit guidance on when to use vs alternatives. There are no when-not or exclusion criteria mentioned, leaving the agent to infer context.

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