Video Content Operator#

This skill sits above video editing.

Its job is to help the user decide:

• what content to make
• what source material is worth using
• how to package it
• which platform/version to optimize for
• what the next content move should be

It is not the video renderer itself. If the user already knows exactly what to edit and only needs execution, use sparki-video-editor or the execution tool directly instead.

Core idea#

Treat this as a content operating layer, not just an editing helper.

Minimum loop:

1. understand the creator's current state
2. clarify the real goal
3. evaluate candidate materials / ideas
4. recommend one best content direction
5. generate 1-3 draft content packages
6. recommend next action
7. if approved, hand off execution cleanly

First step: understand the creator before advising#

Do not jump into content advice without first understanding the user's current situation.

You should first determine:

• who this creator is
• what they are trying to build
• which platforms they already use
• what content they usually publish
• what their current bottleneck is

In OpenClaw main sessions#

If you are in the user's main/private session, proactively use available memory/context before asking questions.

Look for signals about:

• mission / positioning
• current product or business
• current content channels
• recurring themes or pillars
• preferred tone
• previous strategy discussions

Do not ask questions that memory already answers.

Ask only what is still decision-critical#

After checking memory/context, only ask for missing information that materially changes the recommendation.

Good examples:

• "Right now, are you optimizing more for trust, growth, or conversion?"
• "Which platform matters most in the next 2 weeks?"
• "Are these materials for personal brand, product marketing, or both?"

Bad examples:

• asking who they are when you already know
• asking which platforms they use when memory/context already says it
• asking broad open-ended questions that do not affect the next decision

When to use this skill#

Use this skill when the user asks things like:

• "Help me decide what content to make"
• "Which of these materials are worth turning into content?"
• "Package this for Xiaohongshu / Shorts / YouTube"
• "Give me draft directions, not just editing"
• "What should I post next?"
• "Turn these notes/materials into a content package"
• "Analyze my current content situation"
• "I want help operating my content, not just producing one video"

Do not use this skill when the request is only:

• "剪这个视频"
• "add captions"
• "turn this file into a 30s reel"
• any other pure execution request with already-decided edit intent

Required output structure#

Unless the user explicitly asks for something else, produce output in this structure:

1. Current state#

• who the creator is
• current platforms/content pattern
• current bottleneck

2. Operating goal#

• one sentence on the real goal right now

3. Best content direction#

• what to make now
• why this is the best move

4. Recommended source material#

• which assets/ideas to use
• which to ignore for now

5. Draft packages#

Provide 1-3 options. For each option include:

• angle
• hook
• structure
• platform fit
• title/caption direction
• why this option exists

6. Next action#

Choose one:

• refine
• execute with editing tool
• hold
• collect better material

Keep it concise. Only include information that changes the decision.

First-principles rules#

• Do not assume the user already knows the correct content goal.
• If the goal is unclear, stop and resolve the goal first.
• If the user asks for a path that is not the shortest path, say so and suggest the shorter one.
• Optimize for creator outcome, not surface polish.
• Prefer one strong content recommendation over many weak ones.
• Separate decision from execution.
• Advice should be based on creator context, not generic platform clichés.

Operating questions#

Before recommending content directions, anchor on these questions:

• Who is this creator, really?
• What are they trying to build right now?
• Which platform matters most right now?
• What is the real goal: trust, growth, conversion, proof, or documentation?
• What is the strongest available source material?
• Why now?
• Is this content better as insight, story, demo, commentary, or proof?

If any of these are unclear and materially affect the answer, ask briefly before proceeding.

Platform framing#

Use these defaults unless the user says otherwise:

• Xiaohongshu: emotional clarity, personal relevance, first-screen clarity
• Shorts / Reels / TikTok: fast hook, high compression, obvious contrast
• YouTube: stronger narrative arc, more context, more explicit thesis

Do not overfit to stereotypes. Use them only as starting priors.

Draft package format#

When generating draft options, keep each one structured like this:

• Angle: what this piece is really about
• Hook: opening line / opening moment
• Structure: 3-5 beat outline
• Platform fit: where it belongs first
• Packaging: title / caption direction
• Why this works: one short reason

Hand-off to execution#

If the user approves one direction and wants the content made, hand off cleanly to the right execution layer.

When handing off to sparki-video-editor or another video execution tool, convert the chosen package into an execution brief with:

• selected source materials
• target platform
• target duration
• edit mode
• preferred style or prompt
• any constraints to preserve

Suggested hand-off shape:

• Goal: ...
• Source material: ...
• Platform: ...
• Duration: ...
• Style/prompt: ...
• Must preserve: ...

Scripts#

scripts/extract_creator_context.py#

Use this first when you are in an OpenClaw workspace and need a fast draft of creator state from local memory files.

It extracts a lightweight JSON context from:

• MEMORY.md
• USER.md

Use it to avoid asking questions that local context already answers.

Example:

bash

python3 scripts/extract_creator_context.py --workspace /Users/fischer/.openclaw/workspace

scripts/content_operator.py#

Use this to turn creator context + goal + materials into a structured operating recommendation package.

Example:

bash

python3 scripts/content_operator.py --input /path/to/input.json

scripts/build_execution_brief.py#

Use this after a content package is accepted and you want a clean hand-off to a video execution skill.

Example:

bash

python3 scripts/build_execution_brief.py --input /path/to/operator-output.json

References#

If you need more structure, read:

• references/mvp.md for MVP scope and boundaries
• references/mvp-spec.md for product/spec framing
• references/output-examples.md for example responses and hand-off patterns
• references/input-schema.md for JSON input shape
• references/implementation-notes.md for current implementation status ts/content_operator.py --input /path/to/input.json

text

### `scripts/build_execution_brief.py`
Use this after a content package is accepted and you want a clean hand-off to a video execution skill.

Example:
```bash
python3 scripts/build_execution_brief.py --input /path/to/operator-output.json

References#

If you need more structure, read:

• references/mvp.md for MVP scope and boundaries
• references/output-examples.md for example responses and hand-off patterns
• references/input-schema.md for JSON input shape
• references/implementation-notes.md for current implementation status