AcreLens

get_solar_potential

Read-onlyIdempotent

Estimate solar energy production potential for a US address using NREL PVWatts data. Call this when the user asks about solar power viability, off-grid energy, or panel sizing. Returns estimated annual production and a typical installed-cost bracket for the system size you specify (default 5 kW).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_solar_potential"
  }
}

Input Schema

Name	Required	Description
`lat`	No	Latitude of the location.
`lng`	No	Longitude of the location.
`address`	No	US street address (used for geocoding fallback).
`system_size_kw`	No	System size in kilowatts (default 5).

Output Schema

Name	Required	Description
`latitude`	Yes	Latitude used for the calculation. Will be the resolved geocoded value if address was provided instead of lat/lng.
`longitude`	Yes	Longitude used for the calculation. Will be the resolved geocoded value if address was provided instead of lat/lng.
`annual_kwh`	Yes	Estimated annual AC electricity production in kilowatt-hours, from NREL PVWatts.
`cost_bracket`	Yes	Typical installed-cost range (USD) for a system of this size. Indicative only; varies by region and installer.
`system_size_kw`	Yes	System nameplate capacity in kilowatts (echoed from the request, default 5).

Schema Changelog

Changes observed during successful MCP inspections.

First observedMay 6, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds useful context beyond those: it specifies the data source (NREL PVWatts), the return values (annual production and cost bracket), the system size default (5 kW), and the US-only geographic scope, enriching what annotations alone convey.

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 two sentences long, front-loads the core purpose, then covers usage triggers, return content, and default behavior. Every clause serves a purpose, and there is no redundant or filler text.

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

Completeness5/5

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

Given the annotations, output schema, and schema descriptions, the description covers all essential aspects: what it does, when to use it, what it returns, and key defaults. It is fully sufficient for an agent to select and invoke the tool correctly.

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 schema already provides 100% coverage with descriptions for all four parameters. The description's only parameter-related addition is 'default 5 kW' in reference to system size, which duplicates the schema's default field. Thus, it adds minimal extra meaning, matching the baseline of 3.

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 states the tool's purpose with a specific verb ('Estimate') and resource ('solar energy production potential for a US address'). It also distinguishes itself from sibling land-analysis tools by focusing on solar viability and using NREL PVWatts data, making its role unmistakable.

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 explicitly says 'Call this when the user asks about solar power viability, off-grid energy, or panel sizing,' which gives clear context for when to use it. However, it does not mention when not to use it or point to alternatives, so it doesn't quite meet the threshold for a 5.

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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