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

Annotations already establish readOnly/idempotent/non-destructive, so the description sensibly spends its words elsewhere: it discloses the return payload (per-prompt, per-day, totals, everyday equivalents, assumptions, source link) and the interpretive difference between 'onsite' (as vendors report) and 'comprehensive' (wider researcher boundary). That framing is real added context an agent cannot get from the 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?

Front-loads the purpose, then parameters, returns, and routing — no filler sentences. It runs as a single dense prose block rather than separating parameter notes from output notes, which slightly slows scanning, but every clause carries information.

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?

Although there is no output schema, the description enumerates the return contents (per-prompt, per-day and total figures, equivalents, assumptions, source link), covers all four parameters at 0% schema coverage, and routes to the correct sibling. Nothing needed to call it correctly is missing.

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 0%, so the description carries the full documentation burden and meets it: queries_per_day (prompts per day), days (e.g. 250 workdays, 365), usage with concrete Wh/prompt values per enum, and boundary with each enum's meaning. It supplies numeric magnitude for enums that the schema only names.

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?

Opens with a specific verb and resource ('Estimate the water (mL) and energy (Wh) used by chat-style AI prompts') and explicitly names the sibling it is not (estimate_session_footprint) for agentic/coding sessions. An agent can distinguish it from estimate_session_footprint without opening either schema.

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 the use context (chat-style prompts from ChatGPT/Claude/Gemini), an explicit exclusion and redirect ('For agentic/coding sessions use estimate_session_footprint instead'), and the trade-off behind each enum choice. When-to-use and when-not are both stated rather than inferred.

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