AgentFeed

Forecast track record

get_forecast_record

Read-onlyIdempotent

FREE: the live track record of this miner. Every forecast was written down BEFORE its 15-minute window opened and settled afterwards from the exchange public feed, and the raw rows are returned alongside the score so you can recompute it yourself rather than take it on trust. Returns settled count, base rate, Brier skill against climatology, coverage, calibration error and a reliability curve. A backtest is a claim about the past that its author also chose how to compute; this is not that. Free.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`rows`	No	how many raw rows to return, max 500, default 50
`symbol`	No	restrict the record to one symbol

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes	the get_forecast_record payload
`tool`	Yes	the tool that produced this payload

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 25, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "data": {
+      "additionalProperties": {},
+      "description": "the get_forecast_record payload",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "tool": {
+      "const": "get_forecast_record",
+      "description": "the tool that produced this payload",
+      "type": "string"
+    }
+  },
+  "required": [
+    "tool",
+    "data"
+  ],
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description discloses valuable behavioral details: forecasts are written before the window opens, settled from the exchange public feed afterward, and raw rows are returned for independent recomputation. It also notes the output fields and that the tool is free, giving agents a strong safety and trust profile.

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?

The description is front-loaded with the key fact ('FREE: the live track record of this miner') and contains useful details, but it is slightly wordy with the repeated 'Free' at the end and a somewhat rhetorical backtest sentence. It earns a high score but loses a point for minor redundancy.

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 read-only annotations, optional parameters, and existing output schema, the description covers what an agent needs: what the record is, how it was produced, what metrics are returned, and why it can be trusted. No critical call-invocation information appears to be missing.

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 100% and both parameters have clear descriptions. The tool description adds general context about raw rows being returned, but it does not contribute meaningfully beyond the schema's own parameter documentation, so the baseline score of 3 applies.

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 names a specific verb-resource pair ('get the live track record of this miner') and clearly states what is returned: settled count, Brier skill, coverage, calibration error, and reliability curve. It also distinguishes the tool from a backtest, so an agent can understand what this record is and is not without opening the schema.

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 gives clear context for when this tool is appropriate: when you need a verifiable live track record rather than an author-computed backtest. It explicitly contrasts it with backtests ('this is not that') but does not name specific sibling tools or provide a full when-to-use vs alternatives matrix.

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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