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energyai

by com.energyaisolution

check_incentives

Clean-energy incentive guidance for any address WORLDWIDE. US ZIP → federal status + state/utility programs (via DSIRE). Any other country (pass country=) → qualitative, officially-sourced national program guidance. Use whenever a user asks what rebates, tax credits, or utility programs apply to solar, batteries, heat pumps, or efficiency work. [20 anonymous calls/caller/24h; then 100 free calls/key/30d; active Builder required for sustained informational use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoISO 3166-1 alpha-2 country code. Omit for US. Any country works — non-US results return qualitative, officially-sourced incentive guidance (never US federal credits).
zipCodeNoPostal code of the property. US: 5-digit ZIP (ZIP+4 accepted). Other countries: your local postal code (pass country too). Omit entirely for national-level guidance.

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral detail. It discloses the US vs non-US processing difference, data source (DSIRE), qualitative nature of international results, rate limits (20 anonymous calls/24h, then 100 free calls/key/30d), and auth requirement (active Builder). It doesn't detail response format or error handling, but covers the key operational traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: purpose statement, mode-of-use breakdown, explicit usage trigger, and rate-limit/auth constraints—all in approximately four sentences. Every sentence contributes meaningful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's worldwide scope, optional parameters, and lack of an output schema, the description provides sufficient context for correct invocation: it explains when to use, what inputs to provide, what outputs to expect conceptually, and practical constraints. It omits return-format specifics, but that is not required without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% coverage with detailed descriptions for both parameters, including ISO codes, ZIP+4 acceptance, and when to omit each. The tool description adds a bit of value by linking the parameters to result types (federal/state vs national), but does not fundamentally extend beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's purpose with a specific verb ('guidance') and resource ('clean-energy incentives'), and explicitly scopes it 'WORLDWIDE.' It distinguishes US-specific federal/state/utility program detail from non-US qualitative national guidance, making it distinct from sibling tools like get_energy_incentives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage direction: 'Use whenever a user asks what rebates, tax credits, or utility programs apply to solar, batteries, heat pumps, or efficiency work.' It also gives context about rate limits and the active Builder requirement. However, it does not mention alternatives or when not to use the tool.

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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TDQS

C2.8/5.0
Disambiguation2/5

Several tools overlap heavily: get_node_score vs get_energy_node_score, find_local_installers vs match_installers, and route_lead vs submit_contractor_match_request are easy to confuse. The descriptions clarify details, but an agent would often need to inspect arguments to know which installer, incentive, or recommendation tool is the right one.

Naming Consistency3/5

All tool names use snake_case with a verb-leading style, which provides a consistent backbone. However, domain naming is inconsistent: the same concept appears as node vs energy_node, installer vs contractor, and incentive discovery is split across check_incentives, get_energy_incentives, list_guides, and get_guide without a predictable pattern.

Tool Count2/5

29 tools is too many for a single MCP server, especially since several fall into overlapping installer/lead, incentive, recommendation, and commercial-power categories. Many tools appear to be monetization gates or handoff variants that could reasonably be consolidated.

Completeness3/5

The set covers core user journeys: assessment creation/answering/completion, incentive guidance, installer discovery and routing, quote review, and commercial power screens. However, there are notable gaps in state management, such as no way to list or retrieve existing assessments/leads, and several checkout or handoff tools have no follow-up/status tool.

Resources