news_searchSearches the web for news and articles on a topic from the last 7 days (web results recency-filtered; crypto-native headlines merged in when that feed is up)
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals safe read behavior, and the description adds useful behavioral context: results are limited to the last 7 days, filtered by recency, and crypto-native headlines are conditionally merged in 'when that feed is up.' This discloses dynamic data-source behavior beyond the annotation.
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 a single, compact sentence that front-loads the core action and resource, then adds the time window and recency caveat in a tight parenthetical. Every clause earns its place.
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 one-parameter read-only search tool, the description covers the query semantics and result scoping well. It does not describe output structure or pagination, but given the simplicity and absence of an output schema, this is not a major gap.
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?
With 0% schema description coverage, the description must compensate for the single 'query' parameter. It implies that query is the topic phrase to search, which is meaningful, but it does not specify format, length, language, or any special syntax requirements.
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 action and resource: 'Searches the web for news and articles on a topic from the last 7 days.' It includes a helpful temporal scope and recency filter, but it does not explicitly differentiate from sibling tools like sentiment_twitter or filings_search.
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 intended use is implied: use this tool when you need recent web news or articles about a topic. However, there is no explicit guidance about when not to use it or which sibling tool might be preferred for social sentiment, filings, or other news-adjacent data.
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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Tools are grouped by clear prefixes and mostly target distinct resources; market_quotes vs research_token_view, market_top_movers vs market_trending, and funding_current vs market_quotes have some field or purpose overlap, but descriptions draw enough scope boundaries for an agent to choose correctly in most cases. No two tools are truly interchangeable.
All 30 tool names use lowercase snake_case with a consistent domain-prefix convention such as market_, flow_, research_, sentiment_, and catalysts_, making the surface predictable. Even helpers like utc_time and risk_position_size fit the same noun-oriented pattern without style mixing.
At 30 tools this set crosses the 'too many' threshold, and several tools reproduce data already available through broader ones such as research_token_view and market_quotes. The breadth is defensible for a crypto-research platform, but the surface feels heavy and could be consolidated.
The tool set covers the read-only crypto research workflow thoroughly: market data, candles, derivatives, funding, OI, order book, whale flows, ETF flows, on-chain metrics, news, sentiment, prediction odds, technicals, regime/positioning scans, and position sizing. It also includes health and UTC helpers that close practical workflow gaps, with no obvious dead ends.