List Logpush jobs for a specific dataset in a Cloudflare zone (e.g. http_requests, firewall_events).
List Logpush jobs for a specific dataset in a Cloudflare zone (e.g. http_requests, firewall_events).
| Name | Required | Description | Default |
|---|---|---|---|
| zone_id | Yes | required,The ID of the zone | |
| dataset_id | Yes | required,The Logpush dataset ID (e.g. http_requests, firewall_events) |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. 'List' implies a safe read, but it says nothing about pagination, result limits, ordering, or required permissions for a zone-scoped query. For a no-annotation tool this leaves meaningful gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that names the operation and scope with zero filler. It is efficient though minimal; the examples earn their place by clarifying the dataset parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read-only listing with no output schema, the description plus fully documented schema covers the essentials. It is adequate but omits anything about result shape or pagination behavior, and gives no sibling differentiation, so it stops short of complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both required parameters are documented in the schema, including the same dataset examples echoed in the description. The description adds no syntax, ID format, or constraint detail beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (List), resource (Logpush jobs), and scope (a specific dataset in a Cloudflare zone), with concrete dataset examples. It does not, however, explicitly distinguish itself from close siblings like list_logpush_jobs or list_account_logpush_dataset_jobs, so the agent must infer the zone/dataset scoping difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use guidance, no mention of prerequisites (e.g. needing a zone_id), and no routing to alternatives such as list_logpush_jobs for zone-wide listings or the account-scoped variant. The agent gets a description of what the tool returns but not when it should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.