persona-pack

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Build fact-grounded short-form video personas and visual consistency packs from validated benchmark research. Use this when you need to define a repeatable creator archetype, image prompt pack, or persona lock for batch video production. This skill must derive personas from real benchmark evidence such as creator types, protagonist descriptions, visual styles, hooks, and audience language. Do not invent personas or visual traits without source support.

2installs

Sourcepostplusai/postplus-skills

Added on2026-04-30

NPX Install

npx skill4agent add postplusai/postplus-skills persona-pack

SKILL.md Content

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Persona Pack

Follow shared release-shell rules in:

```
postplus-shared
```
release-shell rules

Use this skill when a production workflow needs:

a creator persona recommendation
persona comparison options
a locked visual identity for repeated content
image prompt packs for batch generation

This skill is not for unconstrained character design.

Fact Rule

Personas must be built from observed benchmark evidence.

Use source-backed fields such as:

```
videoCreatorType
```
```
videoProtagonist
```
```
videoVisualStyle
```
```
videoHook
```
lane distribution
strong benchmark subsets
final report conclusions

Do not fabricate:

demographic precision not present in sources
audience fit claims without behavioral evidence
visual traits chosen only because they "look good"

If a detail is inferred rather than directly observed, label it as inference.

Default Workflow

1. Start from strong benchmark subsets

Do not define a persona from the full pool alone if strong benchmark subsets exist.

Prefer:

strong benchmark talking-head videos
lane-specific strong samples
pattern table summaries
final report conclusions

Source Selection Rule

Start from the active project's strongest benchmark artifacts.

If the task clearly belongs to one project or client folder, read from that folder first.

Do not assume one client folder is the default source base for all persona work.

Use the master table and shortlist to extract:

recurring creator types
protagonist descriptors
visual-style descriptors
strong benchmark handles and URLs

Do not let image-model aesthetics override benchmark-supported appearance patterns.

2. Extract persona evidence

Before proposing any persona, collect:

common creator roles
common age feel or life-stage feel if directly implied
recurring wardrobe patterns
recurring environment patterns
recurring camera patterns
recurring speaking style
recurring authority style

Write these as evidence notes first.

3. Recommend the narrowest viable persona

The first persona should maximize:

fit with strongest lanes
repeatability across 10+ videos
visual consistency
credibility for the product

Avoid personas that are:

too broad
too aspirational
too polished and ad-like
unsupported by evidence

4. Produce a persona lock

Every chosen persona should be converted into a stable pack with:

```
personaId
```
```
archetype
```
```
sourceBasis
```
```
appearanceSystem
```
```
outfitSystem
```
```
environmentSystem
```
```
cameraSystem
```
```
voiceStyle
```
```
behavioralConstraints
```
```
negativeConstraints
```

This becomes the upstream source for image generation.

5. Separate direct observation from generation guidance

Use two blocks:

```
Observed from benchmarks
```
```
Prompt translation
```

That prevents prompt language from being mistaken as factual research.

Output Shapes

Common outputs:

persona recommendation memo
3-way persona comparison
final chosen persona lock
image prompt pack
negative prompt pack

Persona Recommendation Memo

Include:

recommended first persona
rejected alternatives
evidence basis
why this persona best fits the first 10 videos

Persona Lock

Should include:

identity summary
repeated visual rules
what must stay fixed
what can vary
what to avoid

Negative Constraints

Always define what not to generate.

Common examples:

too much studio polish
luxury lifestyle look
founder keynote energy
generic influencer glam
overproduced ad lighting

Negative constraints are important because many image models drift toward polished ad aesthetics.

Source Basis Requirement

Every persona recommendation must cite concrete support, such as:

strong talking-head lane distribution
creator-type counts
representative benchmark ids
visual-style descriptions
report conclusions

If the user asks for a persona that is not supported, state that clearly and provide:

closest evidence-backed version
what would need to be researched to support the requested persona