OneQAZ Trading Intelligence

Losing Positions

get_losing_positions

Read-onlyIdempotent

Purpose: Losing paper positions (ROI < 0). Convenience wrapper around get_positions(max_roi=-0.01). Triggers (casual questions too): "what's underwater?", "지금 뭐가 물려 있어?", "show me the red ones", "any positions in trouble?", "얼마나 손실 중이야?". When to call: drawdown / risk review. Prerequisites: none. Next steps: get_position_detail, get_role_analysis. Caveats: paper-trading data only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Max results (default 20)
`market_id`	Yes	Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us 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_losing_positions — 실응답에서 추출(2026-09-23).",
+        "properties": {
+          "common": {
+            "additionalProperties": true,
+            "type": "object"
+          },
+          "common_note": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "filters": {
+            "additionalProperties": true,
+            "type": "object"
+          },
+          "limit": {
+            "anyOf": [
+              {
+                "type": "integer"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "market_id": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "positions": {
+            "items": {},
+            "type": "array"
+          },
+          "returned": {
+            "anyOf": [
+              {
+                "type": "integer"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "stats": {
+            "additionalProperties": true,
+            "type": "object"
+          },
+          "stats_scope": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "total_available": {
+            "anyOf": [
+              {
+                "type": "integer"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "truncated": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "truncated_note": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          }
+        },
+        "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"
+]

Changed3 schema fields changedSep 22, 2026
- addedInput schema / properties / limit / description
```
Added value: +"Max results (default 20)"
```
- addedInput schema / properties / market_id / description
```
Added value: +"Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted)"
```
- addedInput schema / properties / market_id / enum
```
Added value: +[
+  "crypto",
+  "kr_stock",
+  "us_stock"
+]
```
First observedApr 19, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, and openWorld, so the safety profile is covered. The description adds genuinely new behavior: the ROI<0 threshold definition, the 'paper-trading data only' caveat, and the wrapper relationship to get_positions. It stops short of describing result ordering or pagination.

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?

Clearly front-loaded with purpose first, then triggers, prerequisites, next steps, and caveats as scannable labeled sections. The multilingual trigger list is somewhat long but each entry maps to a real query pattern, so it earns its space.

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, return values need no explanation, and the description covers purpose, scope, usage context, prerequisites, downstream tools, and the paper-trading data limitation. Nothing needed to call this correctly is 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 (market_id with enum and aliases, limit with default) are documented in the schema itself. The description adds a max_roi=-0.01 detail, but that parameter is not part of the exposed input schema, so it contributes little to invocation semantics. 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 and defines the exact scope ('Losing paper positions (ROI < 0)'), then anchors it against a sibling by naming get_positions(max_roi=-0.01) as the underlying call. An agent can distinguish it from get_losing_trades, get_profitable_positions, and get_positions without opening any 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?

Provides explicit triggers including casual and non-English phrasings, a when-to-call context (drawdown / risk review), prerequisites, and next steps. The one gap is that it never contrasts 'positions' against the similarly named get_losing_trades sibling, which is the most likely mis-selection.

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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