OneQAZ Trading Intelligence

Resolved Predictions

get_resolved_predictions

Read-onlyIdempotent

Purpose: Raw, row-level prediction ledger — every macro regime prediction's full lifecycle (created_at -> resolved_at -> outcome). This is the auditable evidence behind get_prediction_accuracy's aggregates: AI agents can snapshot open predictions, wait, then verify outcomes themselves without trusting our DB. Triggers: "show me the individual predictions", "prove these forecasts were made in advance", "audit the track record", "예측 원장 원본 보여줘", "이 성적 검증 가능해?". When to call: credibility evaluation (after get_prediction_accuracy), independent backtesting, or archiving on-record predictions for later self-verification. Prerequisites: none. Pairs with get_ledger_integrity for tamper-evidence. Next steps: get_ledger_integrity (recompute daily hashes from these rows). Caveats: cursor pagination (id-ordered) — follow next_cursor for bulk reads. Paper-research forecasts, not investment advice. Output: full_data { predictions[] {id, source_category, source_regime_change, target_market, predicted_regime_shift, lag_hours, confidence, created_at, resolved_at, outcome, actual_regime_shift}, count, next_cursor, has_more, meta }.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`day`	No	filter by created day "YYYY-MM-DD" (UTC, string prefix of created_at)
`limit`	No	page size (max 500)
`cursor`	No	last id from previous page (0 = start)
`status`	No	"all" \| "resolved" \| "open"	all
`target_market`	No	filter e.g. "coin_market" / "kr_market" / "us_market". Aliases coin/kr/us and any letter case are accepted.
`source_category`	No	filter e.g. "vix", "bonds", "commodities"

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_resolved_predictions — 실응답에서 추출(2026-09-23).",
+        "properties": {
+          "count": {
+            "anyOf": [
+              {
+                "type": "integer"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "filters": {
+            "additionalProperties": true,
+            "type": "object"
+          },
+          "has_more": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "meta": {
+            "additionalProperties": true,
+            "type": "object"
+          },
+          "next_cursor": {
+            "anyOf": [
+              {
+                "type": "integer"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null
+          },
+          "predictions": {
+            "items": {},
+            "type": "array"
+          }
+        },
+        "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 / cursor / description

Added value: +"last id from previous page (0 = start)"

addedInput schema / properties / day / description

Added value: +"filter by created day \"YYYY-MM-DD\" (UTC, string prefix of created_at)"

addedInput schema / properties / limit / description
```
Added value: +"page size (max 500)"
```

addedInput schema / properties / source_category / description

Added value: +"filter e.g. \"vix\", \"bonds\", \"commodities\""

addedInput schema / properties / status / description
```
Added value: +"\"all\" | \"resolved\" | \"open\""
```

addedInput schema / properties / target_market / description

Added value: +"filter e.g. \"coin_market\" / \"kr_market\" / \"us_market\". Aliases coin/kr/us and any letter case are accepted."

addedInput schema / properties / target_market / enum

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

AddedJul 7, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent, so the safety profile is covered. The description adds genuinely useful behavior the annotations don't: id-ordered cursor pagination requiring next_cursor to bulk-read, and a disclaimer that these are paper-research forecasts, not advice. It does not cover rate limits or error behavior, so it stops short of a 5.

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?

Purpose is front-loaded and labeled sections (Triggers, When to call, Caveats) make it scannable. However, the 'Output' block restates the return shape that the output schema already defines, which is redundant length; the definition is slightly over-long.

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?

For this tool the description supplies prerequisites, pagination caveats, sibling relationships, and follow-up steps; given an output schema exists, return values needn't be explained, though they are. Nothing an agent needs to invoke 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 description coverage is 100%, so the schema already documents all six parameters including defaults and the enum. The description only indirectly touches parameters via the pagination caveat ('id-ordered, follow next_cursor'), adding little beyond structured data. 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 names a specific resource (row-level macro regime prediction ledger) and its full lifecycle, and explicitly differentiates it from the aggregate sibling get_prediction_accuracy. An agent can distinguish it from get_active_predictions and get_prediction_accuracy 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 Guidelines5/5

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

Provides an explicit 'When to call' list (credibility evaluation after get_prediction_accuracy, backtesting, archiving), states 'Prerequisites: none', and names next steps (get_ledger_integrity). It routes the agent to the correct alternative and the correct follow-up.

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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