get_sample_reportReturn one of the limited public SYA sample report previews for SaaS, API, ecommerce or Web3 websites.
| Name | Required | Description | Default |
|---|---|---|---|
| sample | No | Public sample type | saas |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds context that the reports are 'limited public' and 'previews', which clarifies scope. It doesn't contradict annotations and adds meaningful behavioral context.
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 concise sentence (16 words) that immediately communicates the tool's purpose. No unnecessary words, front-loaded with key 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?
Given the tool has only one optional parameter, good annotations, and no output schema, the description provides sufficient context. It covers the inputs and what the tool returns, making it complete for an AI agent to use correctly.
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% and the description mentions the enum values (saas, api, ecommerce, web3) consistent with the schema. The description does not add significant new meaning beyond the schema's parameter description, so 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 action (Return), the resource (public SYA sample report previews), and the scope (SaaS, API, ecommerce or Web3). It distinguishes from sibling tools like scan_website or list_packages by specifying it returns a sample report preview.
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 implies usage for fetching sample reports but does not provide explicit guidance on when to use vs. alternatives or any prerequisites. There are no exclusions or when-not-to-use details.
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 function: scanning, explaining scores, listing packages, getting links, and sample reports. There is no overlap or ambiguity between them.
All tool names follow a consistent verb_noun pattern (e.g., scan_website, list_packages), making them predictable and easy to understand.
With 5 tools, the server is well-scoped for its purpose of website readiness assessment. Each tool serves a clear role without redundancy or unnecessary complexity.
The tool surface covers the entire workflow: scanning, understanding scores, exploring packages and pricing, and viewing sample reports. No obvious gaps for the stated domain.