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evaluate_events

Evaluate JSON events against Sigma rules to detect and return matches. Supports stateless and correlation engines, with inline or file-based rules and events.

Instructions

Evaluate JSON events against Sigma rules and return matches. Detection-only rules use the stateless engine; collections with correlations use the stateful correlation engine. Rules via inline yaml or path; events via an inline events JSON array or an NDJSON events_path. Optional pipelines and match_detail (off/summary/full).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoPath to a Sigma file or directory. Mutually exclusive with `yaml`.
yamlNoInline Sigma YAML. Mutually exclusive with `path`.
eventsNoInline events as a JSON array of objects. Mutually exclusive with `events_path`.
enrichersNoInline enrichers config (YAML/JSON) applied to results before returning. Mutually exclusive with `enrichers_path`. Only `template` enrichers are supported here; use the daemon for `lookup`, `http`, `command`, and `stix`.
pipelinesNoProcessing pipelines (builtin names or file paths).
events_pathNoPath to an NDJSON file of events. Mutually exclusive with `events`.
match_detailNoMatch-detail verbosity: `off` (default), `summary`, or `full`.
enrichers_pathNoPath to an enrichers config file. Mutually exclusive with `enrichers`.
emit_detectionsNoEmit matches for rules referenced by correlations, including correlations that feed another correlation.
timestamp_fieldsNoExtra event field names to try for correlation timestamp extraction.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.24.0
    • addedInput schema / properties / emit_detections
      Added value: +{
+  "default": false,
+  "description": "Emit matches for rules referenced by correlations, including\ncorrelations that feed another correlation.",
+  "type": "boolean"
+}
  2. Changed1 schema field changedv0.23.0
    • changedInput schema / properties / enrichers / description
      Previous value: -"Inline enrichers config (YAML/JSON) applied to results before returning.\nMutually exclusive with `enrichers_path`. `lookup` enrichers are not\nsupported here (no dynamic-source cache); use the daemon for those."New value: +"Inline enrichers config (YAML/JSON) applied to results before returning.\nMutually exclusive with `enrichers_path`. Only `template` enrichers are\nsupported here; use the daemon for `lookup`, `http`, `command`, and `stix`."
  3. Addedv0.21.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses that engine selection is automatic based on rule type and that inputs are mutually exclusive, but it says nothing about error behavior, permissions, performance, or the shape of the returned matches, which matters for a 10-parameter execution tool with no output schema.

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?

Four compact sentences, front-loaded with the core action and then layered with engine semantics and input modes. Dense but every sentence carries information; nothing is padding, though it leans on terse notation that assumes familiarity with the domain.

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?

With no annotations and no output schema, the description should say more about what a match looks like and how match_detail levels change the response. It also omits any mention of enrichers, emit_detections, or timestamp_fields, which are documented only in the schema. Adequate for selecting the tool, thin for interpreting its result.

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 every parameter is already documented in the schema, including mutual-exclusivity constraints. The description restates a subset (yaml/path, events/events_path, pipelines, match_detail) without adding syntax, defaults, or format detail beyond it, so the baseline of 3 applies.

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

Purpose4/5

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

States a specific verb and resource: 'Evaluate JSON events against Sigma rules and return matches.' That is clearly distinct from parse/lint/validate/convert siblings, which operate on rules rather than executing them against event data. It stops short of explicitly naming the closest alternative (e.g. test_exemplars), so it is clear but not sibling-differentiating.

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?

It gives real routing guidance between the stateless engine for detection-only rules and the stateful correlation engine for collections with correlations, which helps the agent understand execution mode. However, it never says when to reach for this tool instead of test_exemplars, tune_rules, or validate_rules, so the broader when-to-use question is left to inference.

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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