calculate_ev_charging_cost

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

With no annotations, the description bears full responsibility. It discloses that the tool 'Returns cost and hours', which is basic behavioral information. However, it does not elaborate on other aspects like idempotency, latency, or potential side effects. For a calculation tool, this is acceptable but not exceptional. A score of 3 reflects adequate transparency without going beyond the obvious.

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 remarkably concise, consisting of only three short sentences. It front-loads the core purpose and quickly lists inputs and outputs. Every sentence adds value without redundancy. This is an excellent example of efficient communication.

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 low complexity and the existence of an output schema (inferred from 'Returns cost and hours'), the description is reasonably complete. It covers what the tool does, when to use it, and its inputs/outputs. However, the erroneous inclusion of 'charger kW' undermines completeness, and the description lacks information about constraints like charging efficiency or power limits. Thus, a middle score is appropriate.

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?

The input schema covers 100% of parameters with descriptions, earning a baseline of 3. However, the description incorrectly includes 'charger kW' as an input, which is not present in the schema. This discrepancy misleads the user about required inputs, significantly reducing clarity. Therefore, the score is lowered to 2.

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 specifies the tool's purpose: compute electric vehicle charging cost and time to full. It uses a specific verb ('Compute') and resource ('electric vehicle charging cost and time'). It also distinguishes itself from sibling calculators by mentioning its applicability to EV trip planning and referencing list_bundles for related 'energie' calculators.

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 explicitly states 'Use for EV trip planning', providing clear context. It does not state when not to use the tool, but it does direct users to list_bundles for alternative calculators, offering some guidance on alternatives. The lack of explicit exclusions prevents a higher score.

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