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lion_location_solar_enrichment

Location + solar PV potential for sites/properties (?address= or ?lat=&lon=) [x402 paid: GET /api/x402/location-solar-enrichment-json price $0.02 on Base]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNo
lonNo
addressNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed4 schema fields changed
    • removedInput schema / properties / address / description
      Removed value: -"Free-form place/property address to geocode. Provide this OR lat+lon."
    • removedInput schema / properties / lat / description
      Removed value: -"Latitude (-90..90). Use with lon to skip geocoding."
    • removedInput schema / properties / lon / description
      Removed value: -"Longitude (-180..180). Use with lat."
    • addedInput schema / required
      Added value: +[]
  4. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral load; it usefully discloses that this is a paid x402 endpoint at $0.02 on Base and gives the underlying GET route. That cost/payment context is real added value, but it omits auth specifics, whether calls are idempotent, and any response characteristics.

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

Conciseness4/5

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

One compact sentence that front-loads purpose, then input modes, then payment metadata. No filler; every clause carries information.

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

Completeness3/5

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

For a three-parameter tool with no annotations and no output schema, the description covers purpose, accepted inputs, and cost, but says nothing about the returned solar/location fields that an output schema would otherwise supply. Adequate but with a visible gap around return values.

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?

Schema coverage is 0%, so the description must compensate. It does convey the key semantic that address or lat/lon are alternative input modes, which the schema (three flat optional properties) does not express. However, it doesn't clarify that lat and lon must be supplied together, nor any format or range constraints.

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

Purpose4/5

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

The description names a specific resource and combined capability ('Location + solar PV potential for sites/properties'), which an agent can immediately distinguish from the company/domain/sanctions siblings. The verb is implicit (enrichment), but the outcome is concrete.

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

Usage Guidelines2/5

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

There is no statement of when to use this versus other lion_* enrichment tools, nor any prerequisite or exclusion. The only guidance is implicit in the input syntax, which tells the agent nothing about tool selection.

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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