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cf_get_entrypoint_ruleset

Retrieve the ordered list of rules deployed at a Cloudflare zone's entrypoint for a specified phase, showing what actually executes in sequence.

Instructions

Get the ordered list of rules deployed at a zone's entrypoint for a phase.

The "entrypoint ruleset" is the in-line custom ruleset Cloudflare runs
at a given phase. For most WAF/rate-limit investigations this is the
ruleset you want — it shows what's actually executing, in order.

Args:
    zone_id: 32-char Cloudflare zone ID.
    phase: phase name. Common values:
        - http_request_firewall_custom (custom WAF rules)
        - http_request_firewall_managed (managed WAF deployments)
        - http_ratelimit (rate-limiting rules)
        - http_request_sbfm (Super Bot Fight Mode rules)
        - http_request_transform (Transform Rules — request)
        - http_request_origin (Origin Rules)

Calls: GET /zones/{zone_id}/rulesets/phases/{phase}/entrypoint.

Returns: envelope with `data` = the entrypoint ruleset dict including
its ordered `rules[]`.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zone_idYes
phaseYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so the description must disclose behavior. It describes the HTTP GET call, return envelope with data containing ordered rules, and implies read-only safety. However, it does not explicitly mention authentication requirements, rate limits, or confirm it is non-destructive, which would strengthen transparency.

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 Args, Calls, and Returns sections. Every sentence adds value, from the upfront purpose to the concluding return format. It is concise yet thorough, with no filler.

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?

Despite having an output schema, the description explains the return envelope with 'data' and 'rules[]', adding context. It covers both parameters comprehensively and provides usage guidance. Minor omission: no mention of error handling or prerequisites, but overall complete for a simple GET endpoint.

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?

The input schema has 0% description coverage, but the description adds significant meaning: zone_id is '32-char Cloudflare zone ID' and phase includes common values like 'http_request_firewall_custom'. This goes well beyond the schema's simple titles.

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 it retrieves the ordered list of rules at a zone's entrypoint for a phase, distinguishing it from sibling tools like cf_get_ruleset or cf_list_rulesets by explaining the 'entrypoint' concept and its practical use for WAF/rate-limit investigations.

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 explicitly recommends this tool for most WAF/rate-limit investigations, noting it shows executing rules. It lists common phase values but does not explicitly state when not to use it or mention alternatives, though context from sibling tools provides differentiation.

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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