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jmaciasc-google

Google Threat Intelligence MCP Server

get_collection_rules

Retrieve top community and curated hunting rules for a threat intelligence collection, with optional filtering by rule type such as YARA or Sigma.

Instructions

Retrieve top N community rules and all curated hunting rules for a specific collection.

Note: The rule_types argument filters the types of rules returned. Available types are:

  • 'crowdsourced_ids'

  • 'crowdsourced_sigma'

  • 'crowdsourced_yara'

  • 'curated_yara_rule' If rule_types is not provided, all types are returned.

Example:

  • rule_types=['crowdsourced_yara']: Only crowdsourced YARA rules.

  • rule_types=['crowdsourced_ids', 'curated_yara_rule']: Crowdsourced IDS and curated YARA rules.

Args: collection_id (required): The ID of the collection. top_n (optional): The number of top community rules to return from each category. Defaults to 4. rule_types (optional): List of rule types to fetch.

Returns: A list of dictionaries, where each dictionary contains a rule and its metadata, or an error dictionary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNo
rule_typesNo
collection_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations are not provided, so the description carries full burden. It describes the basic return behavior (list of dicts or error) and the rule types filter, but lacks details on side effects, rate limits, or authentication requirements. This is adequate but not richly transparent.

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 well-structured with clear sections (main action, note on rule_types, example, args, returns). Each sentence adds value; the note and example are particularly helpful. No unnecessary fluff.

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?

The tool has three parameters (one required) and an output schema. The description explains the return format (list of dicts with rule and metadata or error) and covers all input semantics. It is complete enough for an agent to understand how to invoke the tool correctly.

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?

With 0% schema description coverage, the description compensates well. It provides meaningful context for each parameter: collection_id (ID of collection), top_n (number of top community rules from each category, default 4), and rule_types (list of types with possible values and an example). This adds significant value beyond the schema's raw types and defaults.

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 retrieves 'top N community rules and all curated hunting rules for a specific collection.' It uses a specific verb ('Retrieve') and resource ('rules for a collection'), and distinguishes it from sibling tools like get_collection_report or get_hunting_ruleset.

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?

No explicit guidance on when to use this tool versus alternatives. While the purpose is clear, the description does not mention when not to use it or compare to siblings like get_hunting_ruleset, leaving the agent to infer usage context.

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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