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weather_energy-region

Degree-days, load signal, and renewables indexes for a US ISO region. Daily heating/cooling degree-days (°F-days), a normalized peak-load signal, and solar/wind generation indexes computed from load-weighted city forecasts for CAISO, ERCOT, PJM, MISO, SPP, NYISO, or ISONE, with extreme-risk flags. [HTTP: GET /v1/energy/:region · price $0.05 via x402 · docs https://x402-factory.com/docs/weather.energy-region]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysYes
regionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations exist, so the description carries full behavioral burden. It does disclose the HTTP method, endpoint, pricing model ($0.05 via x402), and an embedded docs URL – useful operational context. But it omits auth requirements, rate limits, and whether the daily values are forecast or historical. The pricing/path context lifts it above a bare 2.

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 dense but front-loaded sentence delivers the core purpose, then a bracketed operational block. Slightly overloaded with acronyms (ISO/ISO names in caps) and the bracketed metadata, but no wasted sentences.

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?

No output schema exists, so the description must describe return values. It does list the three output families and mentions extreme-risk flags, which is adequate. But without field names, units consistency, or region-specific caveats, an agent cannot fully anticipate the response shape. Adequate but with clear gaps.

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

Parameters2/5

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

Schema description coverage is 0% and the description does not explain either parameter. The params are inferable (region enum is defined in schema; days is a 1-7 window), but the description says nothing about units, valid range, or defaults. With two parameters and no schema-level documentation, the description should have compensated and failed to.

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 states a specific verb-resource pair (energy indexes for a US ISO region), enumerates the three index families returned (degree-days, load signal, renewables), and names the exact region set. No sibling tool covers ISO-level energy indexes, so the agent can distinguish it immediately.

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

Usage Guidelines3/5

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

The description implies usage (per-region energy signals) but never states when to use it versus alternatives like edge_weather-markets or weather_forecast-point. It gives no when-not or exclusion guidance, which is a gap given the crowded weather_* namespace.

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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