get_news_correlationRecent crypto news headlines mentioning an asset (CoinDesk, The Block, Decrypt, Cointelegraph) paired with the 1h price move that followed each. Lets agents filter news bias.
| Name | Required | Description | Default |
|---|---|---|---|
| asset | Yes | Asset ticker, e.g. "BTC", "ETH", "HYPE" | |
| hours_back | No | Lookback window for headlines (default: 24h, max: 7d) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds actionable context: sources (CoinDesk, The Block, etc.), time pairing (1h price move), and bias filtering capability. No contradiction.
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 sentences with no redundancy. First sentence covers core function, second adds filtering capability. Efficiently sized and front-loaded.
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?
No output schema exists, but the description outlines the return structure (headlines paired with price moves). It could be more explicit about the exact fields (e.g., headline text, price change percentage, sentiment bias), but it provides a reasonable mental model for the agent.
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 description coverage is 100%, so parameters are already well-documented. The description mentions 'filter news bias' but does not clarify which parameter enables this, which could be misleading. It adds minimal value 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 it fetches recent crypto news headlines mentioning an asset paired with the 1h price move. It also mentions filtering news bias, distinguishing it from siblings like get_recent_news which likely only provides headlines without correlation.
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 usage when news with price impact is needed, but does not explicitly state when not to use or contrast with alternatives. The sibling get_recent_news provides a natural distinction but is not mentioned.
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.
Many tools are specialized, but several pairs have fuzzy boundaries: e.g., get_funding_rates vs get_top_funding_rates, get_basic_macro vs get_macro_context, get_simple_iv vs get_options_iv. An agent could easily select the wrong one.
Most tools follow a 'get_X' pattern with descriptive noun phrases. There are a few exceptions like 'create_api_key' and 'search_markets', but overall the convention is consistent and readable.
With 47 tools, the server is overloaded. While the domain is broad, this many tools makes discovery and selection difficult for an agent, reducing coherence.
The tool set covers an impressively wide range: macro data, funding, prediction markets, OI history, whale tracking, risk analytics, position sizing, backtesting, and signal generation. It leaves no obvious gaps for a crypto trading assistant.