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NightWatch Live Intelligence

search_tokens

Search for tokens by symbol or name across all monitored exchanges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (e.g. BTC, ETH, DOGE)
exchangeNoFilter by exchange (optional)

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description takes full burden. It discloses that the search spans 'all monitored exchanges', indicating scope. The tool is likely read-only, which is reasonable for a search. No hidden behaviors like destructive actions or auth requirements are mentioned, but the description is sufficiently transparent for a simple search tool.

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?

Single sentence, no wasted words, front-loaded with action and resource. Perfect for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should ideally mention return format (e.g., list of matching tokens with key details). It does not. However, for a search tool, the purpose is straightforward, and the description is minimally complete for basic use.

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% with descriptions for both parameters. The description adds no additional meaning beyond the schema, so the baseline of 3 applies. The description does not explain how the query works (e.g., case sensitivity, partial match) or how exchange filtering behaves.

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 clearly states the tool searches for tokens by symbol or name across all monitored exchanges. This distinguishes it from sibling tools like get_price (which retrieves specific price data) or get_stats (which provides statistics). The verb 'Search' and resource 'tokens' are specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

No explicit guidelines on when to use this tool versus alternatives. The description implies usage for finding tokens by partial name/symbol, but does not instruct when not to use it (e.g., if exact token address or price is needed, other tools like get_token_balance or get_price would be more appropriate). No exclusions or context about prerequisites.

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.