OneQAZ Trading Intelligence

News Leading-Indicator Performance

get_news_leading_indicator_performance

Read-onlyIdempotent

UNVERIFIED — methodology under audit. Do not cite as evidence of predictive capability.

Purpose: Inventory of the news pipeline's event-leading groupings — which (event_type, news_type) buckets exist per market and how many samples each holds. The lead/score metrics themselves are withheld from this response while the calculation method is being audited. Triggers: "what news event groupings does OneQAZ track?", "뉴스 이벤트 분류 어떤 게 있어?", "how many news samples per event type?". When to call: when inspecting news pipeline coverage. This tool does NOT answer questions about predicting or anticipating news — it carries no such evidence. Prerequisites: none. Next steps: get_news_causality_breakdown for the label counts. Caveats: empty when no news events processed in the recent window. Sample counts are coverage figures only; they do not imply statistical validity.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`market_id`	No	Market identifier (crypto, kr_stock, us_stock, etc.). Aliases coin/kr/us and any letter case are accepted.	crypto
`target_market`	No	Alias for market_id (backward compat)
`min_sample_count`	No	Minimum rows-per-grouping cutoff (default 3). A coverage filter only — it confers no statistical validity.

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_news_leading_indicator_performance — 실응답에서 추출(2026-09-23).",
+        "properties": {
+          "indicators": {
+            "items": {},
+            "type": "array"
+          },
+          "meta": {
+            "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"
+]

Changed7 schema fields changedSep 22, 2026

addedInput schema / properties / market_id / description

Added value: +"Market identifier (crypto, kr_stock, us_stock, etc.). Aliases coin/kr/us and any letter case are accepted."

addedInput schema / properties / market_id / enum

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

addedInput schema / properties / min_sample_count / description

Added value: +"Minimum rows-per-grouping cutoff (default 3). A coverage filter only — it confers no statistical validity."

addedInput schema / properties / target_market / anyOf

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

addedInput schema / properties / target_market / description
```
Added value: +"Alias for market_id (backward compat)"
```

addedInput schema / properties / target_market / enum

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

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

First observedApr 19, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/openWorld, but the description adds substantial non-structured context: the metrics are deliberately withheld pending a methodology audit, the result is empty when no news events were processed in the recent window, and sample counts are coverage figures that confer no statistical validity. These are exactly the caveats an agent needs to avoid misreporting output.

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 easy to scan and the most important warning — UNVERIFIED, do not cite — is front-loaded. It is slightly verbose and repeats the 'no statistical validity' point in both the caveat and the schema, but nothing is wasted.

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?

An output schema exists, so return values need no explanation, and the description still covers scope, triggers, exclusions, prerequisites, the sibling handoff, and the empty-result condition. An agent has everything needed to call this correctly and interpret the response honestly.

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 all three parameters (market_id, target_market alias, min_sample_count) are documented in the schema itself, including aliases and the 'coverage filter only' caveat. The description adds no parameter-level meaning beyond that, so the baseline 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?

States a specific verb+resource: an inventory of the news pipeline's (event_type, news_type) groupings per market with sample counts. It also explicitly corrects a likely misconception from the tool name — the lead/score metrics are withheld — and points to get_news_causality_breakdown as the adjacent tool, so the agent can distinguish it from siblings 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 Guidelines5/5

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

Provides concrete triggers ('what news event groupings does OneQAZ track?', 'how many news samples per event type?'), an explicit when-to-call, an explicit when-NOT ('does NOT answer questions about predicting or anticipating news'), prerequisites, and a named next step. This is the full when/when-not/alternative pattern.

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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