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agent-sec

by ai.kernora
OverviewDiscussionsAdmin

get_security_baseline

Return Kernora Agent Security's curated security baseline — the known-good rules an AI coding agent should follow (secrets, injection, supply-chain, destructive ops, data protection). Advisory grounding.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_security_baseline"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description must carry the full burden of behavioral disclosure. It makes clear this is an informational retrieval ('Return') and describes the nature of the content ('known-good rules'). However, it does not explicitly state side effects (e.g., read-only, no modifications) or whether the baseline is static, potentially leaving room for ambiguity.

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 concise and front-loaded: the opening phrase immediately identifies the tool's purpose, followed by a compact list of content areas and a brief purpose statement. Every sentence adds value, and the total length is minimal.

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?

Given the absence of an output schema, the description provides sufficient context by enumerating the domains covered. It also communicates the tool's advisory role. The only notable gap is that it does not mention how the baseline is returned (e.g., format), but for a simple reference tool, the coverage is adequate.

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?

The tool has zero parameters, so there is no parameter semantics to explain. The description correctly uses simple, direct language appropriate for a parameterless tool, aligning with the baseline score of 4 for 0-parameter tools.

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's function with a specific verb ('Return') and names the exact resource ('Kernora Agent Security's curated security baseline'). It elaborates on the contents (secrets, injection, supply-chain, destructive ops, data protection), distinguishing it from the sibling tool 'check_action' which presumably checks individual actions.

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

Usage Guidelines3/5

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

The description implies usage through the phrase 'Advisory grounding,' suggesting the tool is meant to provide a reference for the agent's behavior. However, it does not explicitly state when to use this tool versus 'check_action', nor does it include exclusions or alternative scenarios.

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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