scan_compact
Compact scan returning only rails, capabilities, and a numeric score. Optimized for agent decision-making.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to scan |
Compact scan returning only rails, capabilities, and a numeric score. Optimized for agent decision-making.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to scan |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that only certain data is returned, but it does not mention permissions, error behavior, or any side effects. For a tool with zero annotation coverage, this is a significant transparency gap.
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 two short sentences with no wasted words. Key information is front-loaded ('Compact scan returning...'), making it easy for an agent to quickly parse the tool's purpose and output scope.
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?
With no output schema, the description should explain the return values, but it only names 'rails', 'capabilities', and a numeric score without defining them. This leaves an agent unable to interpret the scan results, making the description incomplete in context.
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 description coverage is 100% for the single 'url' parameter, so the schema already documents it. The description adds no extra parameter-level meaning (e.g., formatting constraints or URL types), keeping the score at the baseline.
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 it is a scan tool returning 'only rails, capabilities, and a numeric score', giving a specific verb and resource plus the output scope. It implies distinctiveness from siblings via 'Compact', but does not explicitly name alternatives, so it falls short of a 5.
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?
Provides clear context with 'Optimized for agent decision-making', indicating when this tool is appropriate. However, it does not give explicit when-not-to-use guidance or name sibling alternatives, so it lacks exclusions.
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.
The tools are largely distinct: scan_url and scan_compact both scan but differ in output detail and purpose, which could cause slight confusion. get_history and validate_x402_json are clearly separate. Overall, descriptions resolve most ambiguity.
All tool names use snake_case and follow a predictable verb_noun pattern: get_history, scan_url, validate_x402_json. scan_compact slightly deviates as verb_adjective but still fits the pattern well.
With only 4 tools, the server is tightly scoped to its purpose—scanning URLs, validating x402 JSON, and retrieving history. Each tool serves a clear need without unnecessary bloat.
The tool set covers the full workflow: scanning (full and compact), validation, and historical access. There are no obvious dead ends—agents can scan, validate, and review past scans without missing functionality.