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NightWatch Live Intelligence

get_price

Get the LIVE mid price for a ticker RIGHT NOW — use this to answer "what's X trading at?", "price of X", "how much is X", or any quote request. Crypto majors (BTC, ETH, HYPE, SOL, ...) via HyperLiquid's main perp dex, AND equities/RWA perps (Samsung 'SMSN', SK Hynix 'SKHX', 'NVDA', 'AAPL', 'TSLA', 'GOLD', ...) via HyperLiquid's builder-deployed equity dex. Returns a numeric price in USD. Null-safe: returns price=null with a note if the symbol is not found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoOptional. 'crypto' (default) = main perp dex; 'equity' = RWA/equity perp dex (Samsung, semis, etc.)
symbolYesTicker, e.g. BTC, ETH, HYPE, or an equity like SMSN (Samsung), SKHX (SK Hynix), NVDA

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It explains the output (numeric price in USD), null-safe behavior (returns null with note if not found), and the dual-dex structure (crypto vs equity). It adds context beyond a minimal description, though lacks details like rate limits or authentication.

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 concise (3-4 sentences) with clear front-loading of the core action. Every sentence adds value: purpose, supported assets, return type, null safety. No fluff 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?

For a simple price tool with no output schema, the description covers return value, error handling (null safety), and both use cases (crypto and equity). It is self-contained and sufficient for correct invocation.

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?

Schema coverage is 100%, baseline 3. The description adds meaning by explaining the market parameter's purpose (crypto vs equity dex) and giving concrete symbol examples (BTC, ETH, SMSN, NVDA). This goes beyond the schema descriptions.

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 uses a specific verb+resource ("Get the LIVE mid price") and clearly distinguishes this tool from siblings. It lists supported assets (crypto majors and equities) and explicitly states it answers quote requests like 'what's X trading at?'.

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 clear usage context by specifying the types of questions it answers (quote requests). It does not explicitly mention when not to use it or name alternative sibling tools, but the context is strong enough to guide correct invocation.

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

A3.8/5.0
Disambiguation3/5

Most tools have distinct purposes, but get_token_intel, get_token_research, and get_microburst overlap in coverage of token intelligence, which could cause agent misselection. Descriptions are detailed but some redundancy exists.

Naming Consistency4/5

Tools follow a consistent verb_noun pattern (agent_*, get_*, search_tokens). Minor deviations like 'get_microburst' and 'get_quartermaster' use less conventional nouns, but overall pattern is clear.

Tool Count5/5

With 15 tools, the count is well-scoped for an intelligence platform covering agent interaction, token data, trading insights, and cross-venue analysis. Each tool serves a distinct purpose without being overwhelming.

Completeness4/5

The set covers identity management, fundamental data, price/market stats, orderbook microstructure, cross-venue verification, and comprehensive token intelligence. Minor gaps like historical data or advanced analytics are omitted, but core workflows are well-supported.