[marketsummary] Trending tokens — the most-mentioned tickers.
timeframe: 24h / 7d / 30d. Free returns the top 3 tickers; the full ranking (top 15 with counts)
unlocks via session_token (from verify_wallet_ownership) OR an x402 payment proof.
| Name | Required | Description | Default |
|---|---|---|---|
| payment | No | ||
| timeframe | No | 7d | |
| session_token | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It clearly explains the free vs. full ranking behavior, including the unlock mechanism via session_token or payment proof, and mentions the timeframe options. This adds valuable context beyond the bare schema.
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?
The description is three sentences, front-loaded with the core purpose, and each sentence adds necessary information: purpose, timeframe, and access tiers. No filler or redundancy.
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?
For a simple tool with no output schema, the description covers key aspects: what it returns (top 3 vs top 15 with counts), how to unlock full data, and available timeframes. It does not detail the exact output structure, but that is not strictly required given the description's clarity.
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?
The schema has 0% parameter description coverage, but the description compensates well: timeframe is explained with allowed values (24h/7d/30d), payment is described as an x402 proof, and session_token is linked to verify_wallet_ownership. It does not specify exact formats, but provides enough to understand purpose and usage.
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 states the tool's specific function: returning trending tokens (most-mentioned tickers). The verb+resource combination is clear, and it distinguishes itself from sibling tools like get_buzz_score or get_attention_shifts by focusing on mention frequency.
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?
The description implies when to use the tool (when interested in trending tokens by mentions) and explains the timeframe options. However, it does not explicitly name alternative tools or state when not to use it, leaving some room for inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct metric or action: attention shifts, buzz score, trending, and narrative tracking measure different facets; longs, shorts, and setups use different strategies; market regime, breadth, and summary are clearly separated. No two tools appear to produce the same output.
All tools follow a consistent pattern: a subsystem prefix (marketsummary__, tokensafety__, verify__) followed by an imperative verb_noun in snake_case. Verbs are predictable (get, find, track, ask, check, request, verify) and objects are clear, making the naming highly uniform.
24 tools is above the typical 3-15 range, but the server covers a broad market-intelligence domain with distinct feature areas. The tools are namespaced by subsystem, which helps agents navigate, but the volume still adds selection overhead.
The set covers market analysis, trending, sentiment, trade setups, token safety, and wallet verification for premium access. Minor gaps exist (e.g., no direct price/OHLC tool or token search), but agents can work around them using the provided tools.