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

Annotations already mark this as read-only/idempotent, but the description goes further by detailing the calculation methodology: usage-based rates, 12-month accumulation accounting for seasonal winter bias, and sorting by estimated annual cost. It also discloses important limitations—raw material cost adjustment varies monthly, government discounts are excluded, and official verification is required—adding significant behavioral context beyond 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?

The description is well-structured with a front-loaded purpose sentence, followed by a concise methodology note and a compact disclaimer paragraph. Every sentence carries relevant information without fluff. The disclaimer is slightly long but justified given the approximate nature of the tool, so it earns a 4 rather than a 5.

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 there is no output schema, the description compensates by stating that results are sorted by estimated annual cost. It also explains the seasonal adjustment and provides caveats about estimate accuracy and support discounts. This is sufficient for a search/comparison tool, though it could mention the plan list structure more explicitly. Overall, it is complete enough for an agent to set expectations.

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 coverage is 100% with each parameter described, so the baseline is 3. The description adds the 'or' relationship between household_size and monthly_m3, but this is already implied by the schema descriptions (e.g., household_size used when usage is unknown). The seasonal variation explanation is a behavioral rationale, not a semantic enhancement of the parameters themselves. Thus it meets the baseline but does not elevate parameter clarity.

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 opens with a specific verb–resource pair: '都市ガスの供給区域と世帯人数（または月間使用量m³）から、ガス料金プランを年間コスト試算つきで検索します' — clearly stating it searches city gas plans by region and household size/usage, with annual cost estimates. It distinguishes itself from siblings by explicitly focusing on gas (vs. hikari/other energy plans) and mentions sorting by annual estimate.

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 clear context for when to use this tool: for searching gas plans with cost estimation, using region and household size or monthly usage. It also sets expectations that results are approximate and should be verified on official sites. However, it does not explicitly name alternatives or state when not to use it, so it lacks explicit exclusions despite the sibling context.

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