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by com.energyaisolution
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verify_forecast

Verify an Energy Odds forecast, free forever: recomputes the hash chain up to that record and returns whether it is intact, when it was logged, its cutoff, and whether it was logged before the cutoff. [always free — no API key required]

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "forecast_id": "us_crude_inventory_weekly/2026-11-13/4"
    },
    "name": "verify_forecast"
  }
}

Input Schema

NameRequiredDescriptionDefault
apiKeyNoOptional existing EnergyAI key for hosts that cannot change Authorization headers. Use it to retain account identity for discovery and get_builder_upgrade_link after a trial. Removed before tool execution and persistence. Omit when the Bearer header is attached; never show the key to the user.
forecast_idYesforecast_id exactly as returned by energy_forecast, e.g. us_crude_inventory_weekly/2026-11-13/4.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, and the description does carry non-trivial behavioral context: it discloses the hash-chain recomputation, the cost model, and that no API key is needed. It does not state whether the call is read-only in effect, what happens for an unknown forecast_id, or how a broken chain is reported, so gaps remain for a tool with zero annotation coverage.

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?

Two sentences, front-loaded with the action and outcome, and the returned fields are enumerated compactly. The bracketed note partly repeats "free forever" from the opening clause, which is minor redundancy but not harmful.

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?

With no output schema, the description correctly takes on the burden of listing the four return values an agent will get back, plus cost and auth requirements. It leaves the failure/edge-case behavior unspecified, which is the main remaining hole.

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 description coverage is 100%, so the baseline is 3: forecast_id is already documented as coming from energy_forecast and apiKey is fully explained in the schema. The description adds no additional syntax or format guidance for forecast_id beyond what the schema already says.

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?

States a specific verb and resource ("Verify an Energy Odds forecast") and immediately pins down the mechanism — recomputing the hash chain up to a given record. That mechanism makes it unmistakable from the sibling energy_forecast, which produces forecasts rather than auditing them.

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?

Usage is only implied through the listed outputs (integrity, log time, cutoff, pre/post-cutoff) — an agent can infer you call it when auditing a forecast's provenance. There is no explicit when-not condition, no mention of what to do when verification fails, and no named alternative.

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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