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cf_query_firewall_events_grouped

Group Cloudflare firewall events by dimensions such as action or country within a specified time range. Retrieve aggregated counts with optional filters and pagination.

Instructions

Group firewall events by chosen dimensions over a time window.

Calls: POST /graphql, firewallEventsAdaptiveGroups dataset.

Args:
    zone_id: zone tag (32-char hex).
    since: RFC 3339 / ISO 8601 start, e.g. '2026-05-28T00:00:00Z'.
    until: ISO 8601 end, must be after `since`.
    group_by: dimensions to group on (e.g. ['action', 'clientCountryName']).
        See _FIREWALL_GROUP_DIMENSIONS for the allowed set.
    filters: extra Cloudflare filter terms (e.g. {'action': 'block',
        'clientCountryName': 'PL'}). Operators like `_in`, `_neq` may be
        appended to the key (e.g. 'action_in': ['block', 'managed_challenge']).
    limit: rows per page, clamped to [1, 500]. Default 50.
    cursor: opaque continuation token from a prior call's `next_cursor`.

Returns: envelope with `data = {rows, count, page}` and `next_cursor`.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zone_idYes
sinceYes
untilYes
group_byYes
filtersNo
limitNo
cursorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description provides good behavioral context: it describes the API call, clamping of limit, and return envelope. It does not mention authentication or rate limits but covers key behavioral aspects.

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 a clear purpose statement, then organized into Calls, Args, and Returns sections. No redundant sentences, every line adds value.

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?

The description covers the key aspects: API call, parameters, return envelope with pagination. It references an external constant (_FIREWALL_GROUP_DIMENSIONS) without definition, which is a minor gap. Output schema exists, but description provides sufficient return structure.

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 the description adds detailed semantics for all 7 parameters, including format hints, allowed values (e.g., group_by dimensions), operators for filters, defaults, and clamping behavior.

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 groups firewall events by chosen dimensions over a time window, specifying the dataset and API endpoint. This distinguishes it from siblings like cf_query_firewall_events_raw.

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?

The description explains the tool's purpose and parameters, and sibling names imply when to use raw vs grouped queries. However, it does not explicitly state when not to use this tool or compare alternatives.

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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