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draft_script

Read-only

Draft a video SCRIPT for the signed-in user, in their own voice, built from what already converts on their own YouTube channel and engineered to fix the opening where they lose viewers. For a long-form video it returns two or three hook options, a beat-by-beat outline, key lines, a CTA, and a suggested title; for a Short, a tight word-for-word script. Call this when the user asks to write, draft, or outline a script (or a hook, intro, or outline) for a video or idea. Pass topic (what the video is about) and optionally format ('short' or 'long'). Klyf Pro only. For titles and thumbnails use package_video; to judge whether an idea is worth making use evaluate_idea; to brainstorm ideas use suggest_ideas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ideaNo
titleNoThe title already agreed for the video, if there is one
topicNoWhat the video is about
formatNoWhether it is a Short or a long-form video; defaults to long-form

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavior beyond that: the shape of the return (hook options, beat-by-beat outline, CTA, suggested title for long-form; word-for-word for Shorts) and a 'Klyf Pro only' gating constraint. It does not contradict the read-only hint since drafting is a generation, not a mutation.

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?

Front-loads the purpose and keeps the routing guidance compact at the end. The middle return-shape sentence is dense but informative; nothing is wasted, though the whole is slightly long.

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?

There is no output schema, so the description carries the burden of describing returns — and it does so reasonably well. With zero required parameters and only the `idea` param left implicit, a caller has enough to invoke it 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 coverage is 75%, so most parameters are documented in the schema. The description reinforces topic and format (including the short/long values and the default), but it never explains the undocumented `idea` parameter or clarifies the interplay between `topic`, `idea`, and `title`. It adds some value without fully compensating for the gap.

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 (draft a video script) and scopes it precisely — in the user's voice, built from converting content on their channel. Explicitly distinguishes itself from package_video, evaluate_idea, and suggest_ideas, 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?

Gives an explicit trigger ('when the user asks to write, draft, or outline a script... or a hook, intro, or outline') and names three alternatives with the conditions that select each. When-to-use and when-to-use-something-else are both covered.

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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