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badchars

living-off-the-land-lolbins-mcp-server

by badchars

analyze_detection_effectiveness

Evaluate detection rules against LOL techniques to measure coverage, estimate false positives, assess bypass risk, and score rule quality.

Instructions

Analyze detection rule effectiveness — rule vs technique coverage, false positive estimation, bypass probability, overall rule quality scoring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesEffectiveness analysis mode
binaryNoBinary name
rule_nameNoDetection rule name or ID to analyze
technique_idNoLOL technique ID
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention any side effects, required permissions, rate limits, or data mutability, leaving the agent unaware of important behavioral traits.

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 a single sentence that efficiently communicates the tool's purpose. However, it lists multiple modes in a dash-separated list, which could be more structured. It is appropriately sized but slightly verbose.

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

Completeness2/5

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

The description does not explain return values, prerequisites, or context for interpreting the results. For a complex multi-mode analysis tool, this leaves significant gaps. The lack of output schema exacerbates the incompleteness.

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?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds marginal value by listing the analysis modes, which correspond to the 'mode' enum, but does not provide any deeper semantics beyond what is in the schema.

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 verb 'analyze' and the resource 'detection rule effectiveness', and lists specific analytical modes (rule vs technique, false positive, bypass probability, rule quality). This distinguishes it from sibling tools like 'assess_detection_gaps' and 'find_detection_blind_spots'.

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?

The description does not provide any guidance on when to use this tool versus alternatives. It lacks explicit when-to-use or when-not-to-use instructions, which is critical given the many sibling tools in the detection domain.

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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