digital-ip-agent

# Digital IP Agent

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

## Workflow

```text
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:

```text
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:

```text
[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.