Australian Heat Pump Hot Water Rebate & Payback
Server Details
Heat pump vs gas hot water (AU): rebate stack, net outlay and payback verdict by postcode.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion between tools. The tool's purpose is clearly distinct by default.
The single tool name 'check_hot_water_switch' follows a clear verb_noun pattern, which is consistent with good naming conventions.
Although the tool count is below the typical 3-15 range, the server's narrow domain (checking rebates and payback for heat pump hot water systems) justifies a single focused tool. It is slightly under but reasonable.
The tool comprehensively covers the main query: it returns stackable rebates, net cost, payback period, and decision drivers. Minor gaps like a separate tool for listing all rebates by state are not essential for the server's stated purpose.
Available Tools
1 toolcheck_hot_water_switchAInspect
Use when someone asks whether a heat pump hot water system is worth it in Australia, which rebates they can stack, how much a heat pump costs after rebates, or how long it takes to pay off — including "can I combine the STC rebate with Victorian Energy Upgrades or Solar Victoria", "do I qualify", and "is a heat pump cheaper to run than gas". Given a postcode, the current hot water system and a few household facts, returns the rebates actually stackable at that postcode (with each scheme's eligibility gates and source), the net-of-rebate outlay, the payback period, and which term — rebates, the avoidable gas supply charge, the energy saving, or a replacement you were buying anyway — is really carrying the decision. Modelled estimate, not financial advice.
| Name | Required | Description | Default |
|---|---|---|---|
| people | No | household size (drives hot water demand) | |
| postcode | Yes | AU postcode — rebate eligibility is postcode-gated | |
| locally_made | No | an eligible locally made unit, which raises the Victorian caps | |
| current_system | Yes | what you have now | |
| owner_occupier | No | tenure — gates the means-tested state rebates | |
| property_value | No | property value — Solar Victoria requires under $3,000,000 | |
| replacement_due | No | true if the existing system is failing and you were replacing it anyway | |
| household_income | No | combined owner taxable income, for means-tested schemes (Solar Victoria caps at $150,000) | |
| system_age_years | No | age of the system being replaced; Solar Victoria requires at least 3 years | |
| building_age_years | No | age of the building; Victorian Energy Upgrades requires at least 2 years | |
| gas_only_for_hot_water | No | true if hot water is your last gas appliance, so the daily supply charge can be avoided |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure. It states the tool returns a 'modelled estimate, not financial advice', which sets expectations. It does not explicitly confirm non-destructiveness, but this is implied by its analytical nature.
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 a single paragraph of about 100 words, front-loaded with usage scenarios and outcomes. All sentences add value, though it could be slightly more structured (e.g., bullet points). It is appropriately sized for the complexity.
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 11 parameters, no output schema, and no annotations, the description adequately covers the tool's high-level function and outputs. However, it lacks details on the exact return format or fields, which would help agents process results. It is minimally sufficient for a tool with this many parameters.
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 has 100% description coverage, so the baseline is 3. The description adds overall context by mentioning the parameter categories ('postcode, current hot water system, household facts') but does not elaborate on individual parameters beyond what the schema already provides.
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: answering questions about heat pump hot water system feasibility in Australia, including rebate stackability, costs, and payback period. It uses specific verbs ('returns', 'use when') and distinguishes the tool by listing concrete scenarios.
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 starts with 'Use when someone asks...' and lists example queries, providing clear context for when to invoke the tool. Since there are no sibling tools, lack of negative guidance or alternatives is acceptable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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