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List Kelp detection rules

list_rules
Read-only

Check which security rules Kelp can enforce before scanning. Filter by rule class to see coverage and answer whether a specific check exists.

Instructions

Returns the catalog of rules Kelp can fire on. Use this to introspect coverage before scanning, or to answer 'does Kelp check X?' without running a scan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
classNoOptional filter to a single rule class.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

The readOnlyHint annotation already flags this as a safe read operation, so the description does not need to repeat that. The description adds a small behavioral nuance by implying it is lightweight ('without running a scan'), but it does not describe the return format, pagination, or any error conditions. Given the annotation coverage, a 3 is appropriate – it adds minimal behavioral context beyond the annotation.

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

Conciseness5/5

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

The description is two sentences with zero redundancy. The main function is stated first ('Returns the catalog...'), followed by the usage guidance. Every word contributes value. It is an exemplary model of concise, front-loaded documentation.

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

Completeness4/5

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

For a simple listing tool with one optional parameter and no output schema, the description provides sufficient information: it states what is returned and when to use it. It does not describe the structure of the returned catalog, but for a list of rules that is probably self-evident. It is complete for an agent to decide when to invoke it, though a more detailed return format would push it to a 5.

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

Parameters3/5

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

The schema fully documents the single optional 'class' parameter with an enum and a description ('Optional filter to a single rule class.'). The description does not mention this parameter at all. Since schema coverage is 100%, the baseline for parameter semantics is 3 – the schema carries the weight, and the description adds no additional meaning beyond that.

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 opens with a clear verb and resource: 'Returns the catalog of rules Kelp can fire on.' This precisely identifies what the tool does. It also distinguishes itself from the sibling scan/explain tools by framing it as an introspection tool for coverage checks, so an agent can tell it apart without reading other definitions.

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

Usage Guidelines4/5

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

The description gives explicit use cases: 'Use this to introspect coverage before scanning, or to answer 'does Kelp check X?' without running a scan.' This tells the agent when to call it. It does not explicitly name alternative tools or state when not to use it, but the context makes the intent clear given the sibling names (scan_path, scan_snippet, explain_rule, explain_finding). A slightly higher score would require naming the alternative explicitly.

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