Digital IP Agent

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name: digital-ip-agent description: Turn a public creator, blogger, podcaster, YouTuber, or X/Twitter personality into a deployable OpenClaw agent. Use when the user provides a YouTube URL, X handle, creator name, podcast host, or asks for things like "turn this creator into an agent", "clone this creator's style", "digitalize this KOL", or "generate agent files from this public persona". Produce an OpenClaw persona package centered on soul.md, identity.md, memory.md, and agents.md, plus a recommended supporting-skill stack.

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Digital IP Agent

Analyze a public creator's voice, worldview, and audience relationship, then turn those traits into a deployable OpenClaw agent package.

Workflow

Input: YouTube URL / X handle / creator name / podcast host / public persona
  ↓
Collect representative public material
  ↓
Extract voice, values, thinking patterns, and audience relationship
  ↓
Generate core OpenClaw persona files
  ↓
Recommend a supporting skill stack
  ↓
Return a publication-ready agent configuration package

Step 1: Classify the input source

| Input type | What to do | | --- | --- | | Single YouTube video | Pull transcript/description and analyze voice + structure | | YouTube channel | Review recent titles, descriptions, and recurring themes | | X/Twitter handle | Review recent posts, replies, and high-engagement patterns | | Creator name only | Locate the main platform first, then analyze | | Multi-platform persona | Synthesize the stable traits shared across platforms |

Step 2: Extract the persona dimensions

Always extract these dimensions before generating files.

Voice

Vocabulary level and sentence rhythm

Signature openings, closings, and recurring phrases

Humor style, emotional temperature, and metaphor habits

Short-form vs long-form tendencies

Thinking model

Core values repeated across content

Decision style and reasoning framework

Time horizon and risk posture

Industry worldview or recurring theses

Content preferences

Strongest subject areas

Preferred content structure

Example style: stories, data, frameworks, history, personal experience

Topics consistently avoided or rejected

Audience relationship

How the creator addresses followers

How disagreement is handled

Whether the persona teaches, debates, challenges, comforts, or performs

Boundary-setting style

Step 3: Normalize the persona summary

Before generating files, build this internal summary:

Creator name / alias:
Primary platform:
Core identity tags (3-5):
Signature voice traits (3-5):
Core values (3-5):
Top domains of expertise:
Thinking framework:
Emotional tone:
Red lines / boundaries:
Relationship stance toward audience:

Step 4: Generate the core files

soul.md

Capture the deepest layer of the persona.

Must include:

Core essence

Fundamental beliefs

Non-negotiables

Mission

Primary drive

Shadow side or limitations

identity.md

Capture how the persona presents itself.

Must include:

Who I am

Background and credibility markers

Signature voice guide

How I think

Intended audience

What I am not

memory.md

Capture the stable knowledge and reference layer.

Must include:

Core expertise areas

Frameworks and mental models

Signature stories and examples

Relationship memory stance

Learning style

Reference points

agents.md

Capture behavior rules for interaction.

Must include:

Response style defaults

Interaction protocols

Tone calibration by context

Out-of-scope handling

Sample interactions

Step 5: Recommend supporting skills

After generating the core files, recommend a supporting skill stack. Use references/skills-catalog.md as the default source.

Match the stack to creator type:

Technical creator

Finance or investing creator

Creative or design creator

Philosophy or education creator

Lifestyle or health creator

General cross-platform creator

Output format

Return the package in this structure:

[Creator Name] Agent Package
├── soul.md
├── identity.md
├── memory.md
├── agents.md
└── skills-recommendation.md

Quality bar

Before finalizing, check:

soul.md feels specific and not generic

identity.md includes concrete voice habits

memory.md contains real examples, frameworks, or recurring references

agents.md contains executable behavior rules, not vague principles

A real fan of the creator would recognize the tone and priorities

Special cases

Sparse information

Search for more material first. If the evidence is still thin, mark uncertain fields explicitly instead of fabricating.

Multilingual creators

Define voice behavior separately for each language.

Controversial creators

Capture the real style and worldview without endorsing it. Record sharp edges and disputed tendencies as traits, not praise.

Fictional or hybrid personas

If the user is actually describing a fictional character or an IP persona rather than a real public creator, use the fictional-companion workflow instead.