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OneQAZ Trading Intelligence

get_symbol_peer_links_tool

Read-onlyIdempotent

Purpose: Symbol-level lead-lag links (e.g. META -> AMZN, lag=15m, rho=+0.53). When symbol is set, only peers that lead or follow that symbol are returned. Triggers (casual questions too): "what moves before NVDA?", "이 종목보다 먼저 움직이는 종목 있어?", "which stocks follow AAPL?", "선행 종목 알려줘", "any early-warning peers for this ticker?". When to call: incorporate peer leading signals into single-symbol reasoning. Prerequisites: none. Next steps: get_signal_detail for the peer's signal context. Caveats: 14-day lookback, 15-minute bars.

Args: market_id: coin / kr_stock / us_stock symbol: Optional. When set, peers are anchored to this symbol. top_k: Number of top links to return

Disclaimer: Information only, not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_kNo
symbolNo
market_idNous_stock

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds behavioral context beyond annotations, including the 14-day lookback, 15-minute bars, and the anchoring behavior when symbol is set. This is useful but not extremely deep, missing details like pagination or output structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized into labeled sections (Purpose, Triggers, When to call, Prerequisites, Next steps, Caveats, Args, Disclaimer) and is front-loaded with the core purpose. It is concise with no filler or repetition.

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?

Given the output schema exists, return-value documentation is not required. The description covers enough context for correct tool selection and invocation: triggers, use case, parameters, caveats, and next steps. The tool is relatively simple, and the description addresses that complexity fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The Args section adds meaning beyond the bare schema by explaining market_id options, the optional symbol's anchoring effect, and top_k as the number of links. With schema description coverage at 0%, this compensation is valuable, though it does not specify constraints like valid ranges for top_k.

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 states a specific verb and resource: 'Symbol-level lead-lag links' with concrete examples like 'META -> AMZN, lag=15m, rho=+0.53'. It clarifies behavior when symbol is set, distinguishing it from other get_* sibling tools by focusing on peer lead-lag relationships.

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?

The description provides explicit triggers, a 'When to call' statement, prerequisites, and a next-step suggestion (get_signal_detail). It does not explicitly mention when not to use this tool or name sibling alternatives, so it stops short of a perfect 5.

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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TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there are overlapping areas such as get_feature_governance_state vs get_feature_governance_status_tool and the convenience wrappers for losing/winning positions/trades. Descriptions clarify relationships well, so confusion is limited.

Naming Consistency4/5

The vast majority follow a consistent 'get_' prefix with descriptive nouns, but inconsistencies exist: some tools have '_tool' suffix (e.g., get_macro_causality_graph_tool) while similar ones do not, and governance tools use 'state' vs 'status_tool'. Overall, the pattern is predictable.

Tool Count2/5

39 tools is excessive for the apparent scope. Many are redundant convenience wrappers (get_losing_positions, get_winning_trades, etc.) that duplicate filters on other tools, and there are near-duplicate governance tools. The count could be significantly consolidated.

Completeness5/5

The tool surface is remarkably comprehensive, covering signals, trades, predictions, positions, macro relationships, news causality, strategies, structure, governance, and ledger integrity. There are no obvious functional gaps, and the tools form a well-integrated evidence chain.