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scout_quickview

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Generate a concise CVE vulnerability summary for any Docker image, with support for JSON or text output and platform selection.

Instructions

Render a compact summary of an image's CVE posture.

args: image - Image reference format - Output format: "json" (default) or "text" platform - Platform of the image to analyze, e.g. "linux/amd64" returns: dict - {"format": , "result": , "raw": }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
formatNojson
platformNo
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. However, it adds the return structure (dict with format, result, raw) which provides basic behavioral transparency. It does not mention any side effects, network requests, or performance characteristics beyond what annotations imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two lines plus arg list). It front-loads the purpose and then lists parameters. The arg list could be slightly more concise (e.g., integrate into prose), but overall it is efficient and scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (3 params, no output schema, many sibling scout tools), the description is adequate but not complete. It explains parameters and return structure but lacks context on how this tool fits relative to siblings like scout_cves (which might return more detailed vulnerability data) or scout_sbom. The return dict description is helpful, but no output schema exists to formalize it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It lists all three parameters with brief but helpful descriptions: 'Image reference', 'Output format: "json" (default) or "text"', and 'Platform of the image to analyze, e.g. "linux/amd64"'. Notably, it explains the platform parameter with an example, which is not obvious from the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Render a compact summary of an image's CVE posture', using a specific verb ('Render') and resource ('image's CVE posture'). It distinguishes itself from sibling tools like scout_cves (which likely provides detailed CVE lists) and scout_sbom (which provides software bill of materials).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives. The description does not mention prerequisites, limitations, or comparisons to sibling tools (e.g., scout_cves, scout_compare). This forces the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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