DexScreener DEX data: search pairs/tokens, get specific pair info, token details by address, trending token boosts.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Blockchain ID, e.g. ethereum, solana, bsc | |
| limit | No | Max results (1-30, default 10) | |
| query | No | Search query (action=search) | |
| action | Yes | ||
| pair_address | No | Pair contract address (action=pair) | |
| token_address | No | Token address, optionally prefixed with 'chain/' (action=token) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does mention the tool returns 'data' but fails to disclose behavioral traits like read-only nature, rate limits, pagination, or error handling. For a data retrieval tool, this is minimally adequate but lacks transparency.
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?
A single sentence covers the core functionality and lists actions without unnecessary words. It is front-loaded but could be better structured (e.g., bullet list) for clarity. No fluff, but brevity sacrifices granularity.
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 moderate complexity (6 params, enum action), no output schema, and no annotations, the description does not explain return values or behavior beyond action types. It is adequate for a straightforward data retrieval tool but leaves gaps for an 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?
Input schema has 83% coverage (likely all but one param have descriptions). The description groups actions but adds little beyond the schema—it does not explain parameter relationships or constraints. With high schema coverage, baseline 3 is appropriate.
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 provides DexScreener DEX data and lists the four actions (search, pair, token, trending). However, it does not differentiate from sibling tools like crypto_market or defi_analytics, which may also provide market data. The purpose is specific but lacks explicit distinction.
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?
No guidance on when to use this tool versus alternatives. The description implies usage for DEX queries but does not mention prerequisites, context, or when not to use it. Sibling tools cover similar domains, making guidance essential.
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.
Multiple tools overlap in providing crypto price data (crypto_price, crypto_market, crypto_derivatives, global_assets) and news (news_feed, tradfi_news). While descriptions clarify some differences, agents may struggle to choose between similar tools.
Tool names mix styles: some are simple nouns (backtest, cn_market), others compound nouns with underscores (crypto_derivatives, derivatives_sentiment). No consistent verb_noun pattern, making it harder to infer purpose from name alone.
With 19 tools covering a broad domain (crypto, DeFi, macro), the count feels slightly high but justifiable. However, several tools could be merged to reduce overlap and improve navigability.
The tool set covers a wide range of market intelligence needs: price data, technical analysis, sentiment, macro indicators, news, and DeFi. Minor gaps like on-chain analytics or direct trading are acceptable given the intelligence focus.