OneQAZ Trading Intelligence

get_structure_validation_history

Read-onlyIdempotent

Purpose: Daily validation history of Level 2 structure predictions (Level 2 = ETF / basket / sector granularity). Each row shows the hit_rate for a specific day, enabling time-series verification of sustained performance. Triggers (casual questions too): "sector accuracy over time?", "구조 예측 매일 검증해?", "daily hit-rate trend?", "요즘 섹터 예측 성적 어때?", "is the sector edge holding up?". When to call: after get_structure_calibration. Prerequisites: none. Next steps: get_monthly_accuracy_trend for the macro-level comparison. Caveats: returns an overall_hit_rate summary across the window.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	Lookback window in days (default 90)
`market_id`	No	Optional market filter. Aliases coin/kr/us and any letter case are accepted.

Output Schema

TableJSON Schema

Name	Required	Description
`full_data`	No
`timestamp`	Yes	RFC3339 UTC, server build time
`disclaimer`	Yes	Canonical compliance disclaimer (always present)
`request_id`	Yes	32-hex per-response correlation id
`is_real_money`	No
`data_classification`	No
`is_investment_advice`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 23, 2026

addedOutput schema / properties

Added value: +{
+  "data_classification": {
+    "anyOf": [
+      {
+        "const": "research_information_only",
+        "type": "string"
+      },
+      {
+        "type": "null"
+      }
+    ],
+    "default": null
+  },
+  "disclaimer": {
+    "description": "Canonical compliance disclaimer (always present)",
+    "type": "string"
+  },
+  "full_data": {
+    "anyOf": [
+      {
+        "additionalProperties": true,
+        "description": "`full_data` for get_structure_validation_history — 실응답에서 추출(2026-09-23).",
+        "properties": {
+          "history": {
+            "items": {},
+            "type": "array"
+          },
+          "meta": {
+            "additionalProperties": true,
+            "type": "object"
+          },
+          "summary": {
+            "additionalProperties": true,
+            "type": "object"
+          }
+        },
+        "type": "object"
+      },
+      {
+        "type": "null"
+      }
+    ],
+    "default": null
+  },
+  "is_investment_advice": {
+    "anyOf": [
+      {
+        "const": false,
+        "type": "boolean"
+      },
+      {
+        "type": "null"
+      }
+    ],
+    "default": null
+  },
+  "is_real_money": {
+    "anyOf": [
+      {
+        "const": false,
+        "type": "boolean"
+      },
+      {
+        "type": "null"
+      }
+    ],
+    "default": null
+  },
+  "request_id": {
+    "description": "32-hex per-response correlation id",
+    "type": "string"
+  },
+  "timestamp": {
+    "description": "RFC3339 UTC, server build time",
+    "type": "string"
+  }
+}

addedOutput schema / required

Added value: +[
+  "disclaimer",
+  "request_id",
+  "timestamp"
+]

Changed5 schema fields changedSep 22, 2026

addedInput schema / properties / days / description

Added value: +"Lookback window in days (default 90)"

addedInput schema / properties / market_id / anyOf

Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]

addedInput schema / properties / market_id / description

Added value: +"Optional market filter. Aliases coin/kr/us and any letter case are accepted."

addedInput schema / properties / market_id / enum

Added value: +[
+  "crypto",
+  "kr_stock",
+  "us_stock"
+]

removedInput schema / properties / market_id / type
```
Removed value: -"string"
```

First observedApr 19, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds useful context beyond annotations, such as the caveat that it returns an overall_hit_rate summary, and explains the daily granularity. No contradiction exists; it enriches the behavioral picture.

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 well-structured with labeled sections (Purpose, Triggers, When to call, Prerequisites, Next steps, Caveats). It is longer than minimal but every section serves a purpose, including the casual triggers that help with natural language matching. It is not overly verbose, so a 4 is fitting.

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?

The description is thorough: it explains purpose, triggers, sequencing, prerequisites, next steps, and caveats. An output schema exists, so return values are already defined. For a tool with two optional parameters, this is complete and leaves no critical gaps for an agent to call it correctly.

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%, with both parameters (days and market_id) already documented. The description does not add meaning beyond the schema—it only implies time range via 'Daily' and doesn't detail syntax or edge cases. Baseline 3 is appropriate.

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 clearly states the tool's purpose: it retrieves daily validation history for Level 2 structure predictions, with each row showing hit_rate. It specifies the resource (validation history) and the verb (implicit get), and it differentiates from siblings by referencing get_structure_calibration and get_monthly_accuracy_trend, showing how it fits into the workflow.

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

Usage Guidelines5/5

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

The description provides explicit triggers, a clear 'When to call' instruction ('after get_structure_calibration'), and a 'Next steps' suggestion. It also includes prerequisites (none) and a caveat, giving the agent comprehensive guidance on when to use this tool versus alternatives.

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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