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by io.github.beepboop2025
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PROOF: the honest track record

proof_backtest
Read-onlyIdempotent

The backtest scoreboard, stated honestly: recall and precision with 95% confidence intervals over labelled funding events, an orthogonal robustness test, every named episode (hits and misses), and the caveats. Use to judge how much to trust the readings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoFalse for a tool failure.
as_ofNo
reasonNo
sampleNo
statusNo
caveatsNo
readingNo
categoryNo
episodesNo
orthogonalNo
event_captureNo
historical_evidenceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": true,
+  "anyOf": [
+    {
+      "required": [
+        "as_of",
+        "sample",
+        "event_capture",
+        "orthogonal",
+        "episodes",
+        "caveats",
+        "historical_evidence",
+        "reading"
+      ]
+    },
+    {
+      "properties": {
+        "ok": {
+          "const": false
+        },
+        "status": {
+          "const": "FAILED"
+        }
+      },
+      "required": [
+        "ok",
+        "status",
+        "category",
+        "reason"
+      ]
+    }
+  ],
+  "description": "Diagnostic scoreboard, misses, caveats, and eligibility boundary.",
+  "properties": {
+    "as_of": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "category": {
+      "type": "string"
+    },
+    "caveats": {
+      "type": "array"
+    },
+    "episodes": {
+      "type": "array"
+    },
+    "event_capture": {
+      "type": "object"
+    },
+    "historical_evidence": {
+      "type": "object"
+    },
+    "ok": {
+      "description": "False for a tool failure.",
+      "type": "boolean"
+    },
+    "orthogonal": {
+      "type": "object"
+    },
+    "reading": {
+      "type": "string"
+    },
+    "reason": {
+      "type": "string"
+    },
+    "sample": {
+      "type": "object"
+    },
+    "status": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive. The description adds content details (recall, precision, confidence intervals, robustness test, episodes, caveats) and honesty framing, which goes beyond the safety profile without contradicting it.

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?

Single well-structured sentence that front-loads 'backtest scoreboard' and lists components concisely. Every element earns its place, no 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 tool has an output schema (not shown but assumed) and annotations cover safety, the description fully explains what the tool provides: metrics, episodes, caveats. No missing information for an agent to decide invocation.

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

Parameters4/5

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

No parameters exist, so schema coverage is trivially 100%. Baseline for 0 params is 4, and description doesn't need to add parameter info. It doesn't, so score is 4.

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?

Explicitly states it's a 'backtest scoreboard' with specific metrics (recall, precision, confidence intervals) and components (robustness test, episodes, caveats). Clearly distinct from sibling tools like crypto_stress_now or latest_article by focusing on the track record.

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?

Provides a clear when-to-use directive ('Use to judge how much to trust the readings'), but does not explicitly state exclusions or name alternative tools. The context is clear enough, though not exhaustive.

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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