Get measured statistics about the x402 ecosystem economy: total 30-day revenue across sampled resources, revenue concentration, revenue at a given rank, price distribution and payer concentration. Free. Use this to decide whether building or buying on x402 is worth it.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the burden of disclosure. It transparently states the tool is 'Free' and uses 'Get measured statistics' to signal a read-only operation, with 'sampled resources' noting coverage limitations. It does not mention auth or rate limits, but these are less critical for a zero-parameter public stats call.
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 efficient sentences: the first fronts the main purpose and enumerates the data content, the second adds the standalone 'Free' fact and a concrete decision use case. Every sentence earns its place without repetition or filler.
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 there is no output schema, the description names the key returned statistics (revenue, concentration, distribution, payer concentration) and gives a reason to call it. It does not describe exact output formatting or data freshness, but for a zero-input market-stats endpoint this is largely sufficient.
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 tool has zero parameters, so the schema is fully covered vacuously. The baseline for 0-parameter tools is 4, and the description's list of statistics provides useful context even though no parameter details are needed.
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?
States a specific verb ('Get') and resource ('measured statistics about the x402 ecosystem economy'), then enumerates exact output dimensions: 30-day revenue, revenue concentration, revenue at rank, price distribution, payer concentration. This clearly sets it apart from sibling tools like x402_gas_price or x402_verified_merchants.
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 gives a clear use case: 'Use this to decide whether building or buying on x402 is worth it.' It also notes the tool is 'Free,' which helps an agent choose it over a paid alternative. It does not explicitly name sibling alternatives or exclusion conditions, so it stops short of a 5.
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 targets a distinct aspect of the x402 ecosystem: endpoint liveness, deep merchant audit, facilitator comparison, gas pricing, market analytics, and verified merchant listings. There is no real overlap between tools.
All tools share the x402_ prefix and snake_case, but only audit_merchant and check_endpoint follow a verb_noun pattern. The remaining tools are noun phrases like gas_price, market_stats, and verified_merchants, making the naming conventions mixed yet still readable.
Six tools is well-scoped for an ecosystem intelligence server. Each tool fills a distinct niche and none feel redundant or superfluous.
The tool set covers the entire discovery and research workflow for the x402 economy: checking endpoints, finding verified merchants, auditing merchant trustworthiness, choosing facilitators, estimating gas costs, and assessing market viability. No obvious dead ends or critical gaps.