vibe_edit_landing_page

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

No annotations are provided, so the description carries the full burden. It explicitly discloses that 'it does NOT change anything by itself' and returns only an operationId. It also reveals the async nature (polling) and that vibe-edit sessions reside in a separate store from the generic job queue. This is rich behavioral context that fully informs the agent about side effects and operational expectations.

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?

The description is long but well-organized with numbered steps and inline flow annotations. Every sentence contributes to understanding the multi-step process, but the density of information makes it slightly heavier than strictly necessary. It is efficient for the complexity, though a bit over the ideal minimal size.

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 tool with no output schema, the description masterfully covers the full lifecycle: returns operationId, how to poll, what to expect in the changes array, and how to proceed to apply and publish. It also handles edge cases like the separate store and sectionId requirements. The agent has everything needed to use this tool correctly without external documentation.

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 description coverage is 100%, so the baseline is 3. The description reinforces the scope-sectionId dependency and lists example section keys, but these are already present in the input schema. It adds workflow context rather than new parameter-level semantics, so it doesn't elevate above the baseline.

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?

The description clearly states the tool's purpose: 'Use AI to propose an edit to a landing page based on natural-language instructions.' It also explicitly frames this as 'step 1 of a propose → review → apply flow', which distinguishes it from sibling tools like apply_vibe_edit and edit_landing_page. The verb, resource, and scope are all specific.

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?

The description provides an explicit step-by-step workflow: call this tool, poll get_vibe_edit_status (NOT get_job), review the changes array, call apply_vibe_edit, then publish_landing_page. It also clarifies when scope='section' requires sectionId. This goes beyond generic guidance by naming the exact alternative to avoid (get_job) and explaining the separate store, making the usage context unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.