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msadigo

mcp-hayabusa

by msadigo

get_hayabusa_rules

List Hayabusa or Sigma detection rules, optionally filtered by keyword. Use to preview which rules will match a given filter for scan_evtx.

Instructions

List available Hayabusa/Sigma detection rules, optionally filtered by keyword.

Useful for understanding what rules exist before running scan_evtx — e.g. call with keyword="mimikatz" to see which rules would be loaded by scan_evtx(rule_filter="mimikatz"), since both use the same case-insensitive match against rule file text.

Args: keyword: Only return rules whose rule file text contains this string (case-insensitive), e.g. "lateral" or "mimikatz". Omit to list all rules (subject to max_results). rules_dir: Optional path to a custom Sigma/Hayabusa rules directory. Defaults to Hayabusa's bundled ./rules. max_results: Cap on the number of rules returned (default 50). total_matched in the response is always the true match count.

Returns: A dict with total_matched (true count of matching rule files) and rules: a list of {path, id, title, level, status, description, author, tags, logsource}, capped at max_results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNo
rules_dirNo
max_resultsNo
Behavior4/5

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

Without annotations, the description carries full burden. It discloses case-insensitive matching, default max_results (50), and the meaning of total_matched. It does not mention read-only nature or auth requirements, but for a listing tool, this is sufficient.

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?

Well-structured: purpose sentence, usage paragraph, then bulleted parameters (though not in markdown), and return format. Every sentence adds value with no repetition.

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

Completeness5/5

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

Covers all aspects: inputs, outputs, relationship to sibling, example usage, default behaviors. Given 3 optional params and no output schema, the description is fully complete.

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

Parameters5/5

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

Schema coverage is 0%, but description compensates fully: explains keyword filtering (case-insensitive, examples), rules_dir default path, and max_results cap with response field clarification. Each parameter gets detailed, contextualized meaning.

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 'List available Hayabusa/Sigma detection rules, optionally filtered by keyword.' It identifies the specific verb (list) and resource (rules), and distinguishes from sibling tool scan_evtx by explaining the relationship.

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?

Explicitly states it's 'useful for understanding what rules exist before running scan_evtx' and provides an example with keyword='mimikatz'. It could be improved by mentioning when not to use (e.g., for scanning logs), but the guidance is clear.

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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