Fetches the top 15 cryptocurrencies sorted by 24h price change. Includes price, market cap, and percentage move. Source: CoinGecko/CoinLore. Cache TTL 30s. Use when the agent needs to surface notable crypto market moves.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, and idempotent hints. The description adds valuable context beyond annotations: data source (CoinGecko/CoinLore), cache TTL (30s), and output contents (price, market cap, percentage move). No contradictions.
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?
Three concise sentences, front-loaded with purpose and data scope, followed by supported details. Every sentence earns its place with no 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, parameterless read-only tool with no output schema, the description covers purpose, return contents, source, caching, and intended use. It is complete and self-contained.
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?
Tool has zero parameters, so the baseline is 4. The description adds no parameter info, but none is needed; schema coverage is trivially 100%.
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 fetches the top 15 cryptocurrencies sorted by 24h price change, with a specific verb and resource. This distinguishes it from sibling tools like tf_btc_price and tf_fear_greed.
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?
Provides explicit usage context: 'Use when the agent needs to surface notable crypto market moves.' While it doesn't name alternative tools or exclusions, the context is clear and actionable.
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 clearly distinct purposes (e.g., tf_btc_price vs tf_fear_greed), but there is some overlap between free and premium aggregated tools (e.g., tf_briefing, tf_premium_briefing, tf_premium_agent_context). However, descriptions explicitly differentiate them by content and cost.
All tools follow a consistent pattern: 'tf_' prefix (with 'tf_premium_' for premium ones) and snake_case. Names are descriptive and predictable, e.g., tf_btc_price, tf_earthquakes, tf_premium_macro.
27 tools is on the high side, but the server covers a broad domain (crypto, finance, earthquakes, AI trends, payment system, etc.). Each tool serves a specific purpose, so the count is borderline acceptable but feels slightly heavy.
The tool surface covers a wide range of data feeds: crypto, forex, macro indicators, earthquakes, HN, HuggingFace, prediction markets, payment system, and service status. Minor gaps exist (e.g., no dedicated stock prices tool beyond premium macro, no weather), but overall it's comprehensive for a terminal feed.
