Get top trending market narrative sectors — AI, RWA, DePIN, memecoins with momentum and top tokens (top 3 free) — Trending market narratives (e.g. AI, RWA, memecoins, DePIN) derived from CoinGecko Categories with their leading tokens. Free preview: top 3 narratives (3 tokens each); the full set requires a Weekly Alpha subscription. Cached ~30min.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavioral traits: data derivation (CoinGecko Categories), caching interval (~30min), and access limitations (free vs. subscription). No contradictions present.
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 relatively concise but slightly repetitive (mentions 'trending market narrative sectors' twice). Key information is front-loaded, and every sentence adds value.
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 parameters and no output schema, the description explains what the tool returns (top narratives and tokens) and limitations. However, it does not describe the output structure or format, which would be helpful for a complete picture.
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 tool has zero parameters, so schema coverage is 100% and the description adds no parameter detail. Per guidelines, baseline is 4 for no parameters, and the description does not need to compensate.
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 retrieves top trending market narrative sectors with leading tokens, listing examples (AI, RWA, DePIN, memecoins) and specifying the data source (CoinGecko Categories). This distinctly differentiates it from siblings like narrative_history, which provides historical data.
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 does not explicitly state when to use this tool versus alternatives. It mentions the free preview limitation but lacks guidance on context or exclusions relative to similar tools like trending or market_context.
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.
Most tools have distinct purposes, but there are a few pairs with overlapping boundaries (e.g., analysts_signals vs analysts_signals_all, whale_movements vs whale_movements_summary) that could cause minor confusion.
Naming is predominantly snake_case and descriptive, with minor inconsistencies in plural/singular forms (e.g., 'analysts' vs 'analyst_archive'). Overall pattern is stable.
With 55 tools, the server is quite heavy. While the scope is broad, many tools are history/monthly variants that could be combined, making the count feel inflated beyond what is ideal for a single server.
The tool set covers a wide range of crypto analytics domains (analysts, arbitrage, funding, whales, sentiment, etc.). Minor gaps exist (e.g., no direct token price endpoint), but overall it's a comprehensive surface.