OneQAZ Trading Intelligence

Symbol Context

get_symbol_context

Read-onlyIdempotent

Use when the question is about one stock or coin — its current signal state, the OneQAZ structure group it belongs to, and which assets have tracked lead-lag links to it. Returns self-contained headline claims first, then the symbol's observed state, upstream links (its group, macro/ETF/basket instruments and symbols that move before it), peers (symbols that follow it), tagged news, and gaps that say what is not tracked. Not for sector-wide questions (use get_group_context) or whole-market questions (use get_market_context). Provides regime, signal-score and linkage context with sample sizes and measured hit rates; every link carries its evidence and every empty section is listed in gaps. Not a real-time quote, fundamentals, or full-text news source. Accepts tickers, KRX codes or names; ambiguous inputs return candidates instead of a guess.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Max links per section (default 8, max 50).
`symbol`	Yes	Ticker (NVDA), KRX 6-digit code (005930), coin base ticker (BTC) or name (삼성전자, Samsung Electronics). Ambiguous names return candidates, not a guess.
`question`	No	Optional. The user's original question, used only for service improvement analytics. Does not change the response.
`market_id`	No	Optional. crypto / kr_stock / us_stock (aliases coin/kr/us). Narrows name resolution.

Output Schema

TableJSON Schema

Name	Required	Description
`gaps`	No
`meta`	No
`news`	No
`self`	No
`peers`	No
`entity`	No
`headline`	No
`upstream`	No
`timestamp`	Yes	RFC3339 UTC, server build time
`disclaimer`	Yes	Canonical compliance disclaimer (always present)
`downstream`	No
`request_id`	Yes	32-hex per-response correlation id
`resolution`	No
`data_classification`	No
`is_investment_advice`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 16, 2026

addedInput schema / properties / question

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Optional. The user's original question, used only for service improvement analytics. Does not change the response."
+}

AddedOct 15, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, it discloses the response ordering (headline claims first), the section inventory including 'gaps' for untracked items, and that links carry sample sizes, measured hit rates and evidence. It also states negative capability boundaries — not a real-time quote, fundamentals, or full-text news source — which is behavioral context annotations cannot convey.

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?

It is front-loaded with the usage trigger, then the return shape, then the exclusions, which is the correct order. The single dense paragraph packs a lot, and a couple of clauses (the repeated ambiguous-input note) could be trimmed, but almost every sentence earns its place.

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?

Even though an output schema exists and return values need not be described, the description still gives an accurate section-by-section map of the response plus explicit scope limits. For a read-only, single-symbol context tool this leaves nothing an agent needs 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%, so the schema already documents limit, symbol formats, question and market_id. The description restates the ticker/KRX/coin-name acceptance and the ambiguous-input behavior, which the schema also states, adding reinforcement but no new semantics. Baseline 3 applies when the schema does the heavy lifting.

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 verb+resource and enumerates exactly what is returned: current signal state, OneQAZ structure group, and lead-lag linked assets. It explicitly distinguishes itself from get_group_context and get_market_context, so an agent can separate it from siblings without reading schemas.

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?

It gives a precise trigger ('when the question is about one stock or coin') plus explicit exclusions with named alternatives for sector-wide and whole-market questions. It also documents the fallback behavior for ambiguous input (candidates instead of a guess).

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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