The unanimous club — tokens listed on ALL monitored exchanges (the strongest listing consensus signal). Returns the full club list with grades. Pass an optional symbol to check membership for one base ticker.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | No | Optional base ticker to check membership (e.g. BTC) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description indicates read-only behavior (returns lists) but does not disclose any additional behavioral traits like potential rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two well-structured sentences. First defines the tool's concept, second explains output and optional parameter. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description sufficiently explains return of full club list with grades and optional membership check. No critical missing context for this straightforward tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage for the single parameter. Description adds value by explaining that the symbol checks membership for one base ticker, enhancing understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns tokens listed on all monitored exchanges (the strongest listing consensus signal) with grades. It distinguishes itself as the 'unanimous' club among siblings like get_microburst, but does not explicitly contrast use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description mentions optional symbol parameter for membership check, implying use for consensus signals. No explicit guidance on when not to use or alternatives among siblings.
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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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.
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.
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.
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.