OneQAZ Trading Intelligence

Structure Validation History

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.

Changed1 schema field changedOct 7, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```

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

A4.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=true, so the safety and repeatability profile is covered. The description adds a scoping caveat (the window includes an overall_hit_rate summary) and the daily-row shape, but discloses nothing about auth needs, latency, or data-freshness behavior beyond that.

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 labeled sections (Purpose / Triggers / When to call / Prerequisites / Next steps / Caveats) are front-loaded and scannable. The trigger list is long, but it earns its place by enabling intent matching against casual queries; only slight verbosity keeps it from a 5.

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?

With an output schema present, the description need not explain return values, and it still covers prerequisites, next steps, caveats, and routing context. For a read-only history tool, an agent has everything needed to select and 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%, and both parameters (days, market_id) carry their own descriptions including the alias handling. The description implies a lookback window ('over the window') but adds no syntax or constraint detail beyond the schema, so the baseline 3 holds.

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 ('Daily validation history of Level 2 structure predictions') and even disambiguates the domain term ('Level 2 = ETF / basket / sector granularity'). It tells the agent what each row contains (hit_rate per day), making it clearly distinguishable from siblings like get_performance_metrics or get_prediction_accuracy.

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?

Explicitly states 'When to call: after get_structure_calibration' and 'Next steps: get_monthly_accuracy_trend for the macro-level comparison', routing the agent to alternatives by condition. The Triggers block with casual and multilingual questions further pins down when it applies.

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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