Live crypto market pulse + Base mainnet chain snapshot (BTC/ETH/SOL/USDC prices with 24h change, block height, gas price). Payment: $0.001 USDC on Base via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| include | No | Optional subsets: market, chain |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose a critical operational detail—payment of $0.001 USDC on Base via x402—and lists the data returned, which adds value. However, it does not explain what happens on payment failure, rate limits, or other runtime behaviors beyond the data content.
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 extremely concise: two sentences. The first sentence front-loads the core purpose and data scope, while the second clearly states the payment requirement. There is no filler or redundant information.
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 tool with no output schema and no annotations, the description conveys the key return categories (market prices, 24h change, block height, gas price) and the payment prerequisite. It is adequate for an agent to invoke, though it could be more explicit about the exact output structure or potential error conditions. Given the absence of structured metadata, this is a reasonably complete description.
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 input schema already defines the 'include' parameter with full descriptions ('Optional subsets: market, chain'), so schema coverage is 100%. The description adds context by mapping these subsets to the actual data items (prices, block height, gas price), but it does not introduce new parameter semantics beyond what the schema provides.
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 that the tool provides a live crypto market pulse and Base mainnet chain snapshot, listing specific assets and metrics (BTC/ETH/SOL/USDC prices, 24h change, block height, gas price). It distinguishes from siblings by naming these data points, but lacks an explicit imperative verb like 'get' or 'retrieve', making the purpose slightly implied.
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 is provided on when to use this tool versus alternatives such as crypto_market_pulse_sample or usdc_on_base_stats. The description does not mention any exclusions, selection criteria, or scenarios where a sibling tool would be more appropriate.
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.
Each tool has a clearly distinct purpose: crypto market data, free sample, DNS lookup, URL extraction, JSON repair, and USDC analytics. Even the two crypto tools are differentiated by the free sample variant.
All tool names follow a consistent snake_case pattern with a noun_verb or descriptive style (e.g., crypto_market_pulse, dns_lookup, extract_urls). No mixed conventions.
Six tools is a reasonable count, though the server covers a wide range of utilities from JSON repair to crypto analytics. The count is appropriate but the scope feels slightly scattered.
For a utility server, the coverage is adequate: it provides core functions like JSON repair, DNS lookup, and URL extraction. Minor gaps exist (e.g., no generic text processing), but the stated utilities are well covered.