sweepOne verify-loop lane: confidence-labeled findings on any topic. The flagship teaser — full sweeps at $0.50-5 ship when this crosses BUILD. [price: $0.05/call USDC via x402]
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Research topic |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does reveal the price and that findings are confidence-labeled, but it does not state whether the tool is read-only, how output is returned, what the verify-loop lane means, or any limitations. The unexplained 'BUILD' and 'full sweeps' references add confusion rather than 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?
The first sentence is relatively compact, but the second sentence and bracketed price are promotional and not useful for tool selection or invocation. 'The flagship teaser — full sweeps at $0.50-5 ship when this crosses BUILD' should not be in a tool definition. The description would be more effective if reduced to one functional sentence.
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?
Even with only one parameter and no output schema, the description leaves the agent without a clear contract. It never defines 'sweep', 'verify-loop lane', or 'BUILD', and it does not explain what a result looks like. The price is the only concrete operational detail, but the overall definition is too vague to fully support correct invocation.
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 coverage is 100%: the only parameter, topic, is described as 'Research topic.' The description adds that findings are 'on any topic,' implying no restrictions on the topic value, but it provides no format, examples, or additional constraints. The baseline 3 applies because the schema already documents the single parameter adequately.
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 says the tool produces 'confidence-labeled findings on any topic,' which gives a vague sense of a research/verification tool, but it never names the action (search, analyze, verify) or defines what a 'sweep' is. The 'flagship teaser' phrasing is promotional, not functional, and does not differentiate it from research siblings like search_verify, scrape, or sentiment.
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 given about when to use this tool versus its alternatives. Sibling tools are not mentioned, and 'any topic' implies broad applicability without any criteria for when sweep is preferred over other research/verification tools. An agent must guess when to invoke it.
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.
Most tools have distinct purposes, but several clusters overlap: domain_facts, page_meta, and scrape all return page title information, and search_verify, hallucination_check, and sweep all target claim validation. The descriptions usually clarify the use case, but the boundaries are not always obvious.
All names use lowercase snake_case, so there is a baseline consistency, but the pattern is mixed: bare verbs like scrape, summarize, and sweep sit alongside noun+noun forms like domain_facts and noun+verb forms like entity_find. The names are readable but do not form a predictable verb_noun API convention.
At 26 tools, this is heavy and above the typical well-scoped 3-15 range, though the server is explicitly positioned as a broad shelf of paid utilities. Many tools are small one-purpose endpoints, so the count feels more like a catalog than a focused suite, but it is not an extreme mismatch.
The shelf covers the major advertised areas: web page analysis, research verification, text guards and NLP, blockchain reads, and image generation. There are some gaps such as no web search and no transaction sending, but agents can typically work around them or pair this with another server.