XCut AI – Viral Content Research

Run an XcutAI playbook

xcut_run_playbook

Use this when the user wants a ready-made content deliverable from what is on their canvas: a month or week content plan, 25 hooks, 3 scripts, breakout remix, competitor teardown or benchmark, prospect audit, ad-angle gap map, ad creatives, carousel or thumbnail concepts. Token-billed (a month plan is roughly 60-90 credits). Longer runs return a job_id. Do not use for a single custom request (use xcut_write_content).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "playbook": "<playbook>"
    },
    "name": "xcut_run_playbook"
  }
}

Input Schema

Name	Required	Description
`days`	No	Plan length, for month/week plans.
`notes`	No	Extra instructions from the user.
`platform`	No	The platform to write for, when the playbook follows one.
`playbook`	Yes	month or week (content plan), hooks (25 hooks), scripts (3 scripts), remix (breakout remix), teardown, benchmark, audit (prospect audit), angles (ad-angle gap map), adcreatives, carousel or thumbnails.
`canvas_id`	No	Optional. Leave it out unless the user names a canvas: XcutAI then uses their "From AI apps" canvas, where imports also land. Ids come from xcut_list_canvases.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 9, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false), so the bar is lower. The description adds meaningful non-schema behavior: token billing with a concrete cost estimate (a month plan ~60-90 credits) and that longer runs return a job_id (async). It stops short of noting that re-running bills again (relevant given idempotentHint=false) or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and scope are front-loaded and the exclusion is last, which is a sensible order. The first sentence is a long comma-list of deliverables that is dense but earns its place by conveying the tool's breadth; still, it could be tightened.

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?

For a costly, non-idempotent generation tool with no output schema, the description supplies the essentials: what it produces, when to use it vs a sibling, the billing implication, and that longer runs return a job_id (implying polling via xcut_get_job). An agent has enough to call and follow up correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter is already documented, and the baseline is 3. The description restates the playbook values rather than adding syntax or format meaning beyond what the schema's own playbook description provides.

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?

States a specific verb+resource (run a playbook) and enumerates the concrete deliverables the playbooks produce (month/week plan, hooks, scripts, teardown, audit, etc.). It distinguishes itself from siblings by naming xcut_write_content as the alternative for single requests, so an agent can route without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use (user wants a ready-made deliverable from canvas content) and explicit when-not ('Do not use for a single custom request (use xcut_write_content)'). The alternative tool is named, leaving nothing to inference.

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

All XCut AI – Viral Content Research tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?