A customer-research tool that creates fictional panels of varied customer types, interviews them separately, and summarizes their answers. It can explore motivations or test specific product ideas and messages.

Use it to build reusable customer panels, ask about needs and buying decisions, compare product concepts or offers, and review themes, charts, and representative answers.

It helps you get early feedback before spending time and money on field research. Separate interviews and grouped themes make it easier to compare viewpoints and spot common concerns.

persona — Skill for Claude Code by takechanman1228/claude-persona

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/takechanman1228/claude-persona

agentmods

npx agentmods add skills/takechanman1228/claude-persona/persona

Made for: Claude Code.

Or install claude-persona, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/takechanman1228/claude-persona/persona/github.svg)](https://agentmods.dev/skills/takechanman1228/claude-persona/persona)

Your own site

<a href="https://agentmods.dev/skills/takechanman1228/claude-persona/persona"><img src="https://agentmods.dev/badge/skills/takechanman1228/claude-persona/persona/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/takechanman1228/claude-persona/persona"><img src="https://agentmods.dev/badge/skills/takechanman1228/claude-persona/persona.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 104 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 7,210 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00104	$0.07210
Opus 5.5	$0.00042	$0.02884
Sonnet 5.5	$0.00021	$0.01442
Haiku 4.5	$0.00010	$0.00721

Measured 2mo ago against content hash fbc741012554, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

persona scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/persona/SKILL.md · 675 lines

How it starts

The opening of the file, as written. The whole thing — 675 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Persona Panels for Customer Research

Build reusable persona panels, ask open-ended customer questions, and run concept tests on messages, offers, and product ideas.

3-Step Workflow

Inspired by TinyTroupe (Generate Personas → Simulate Interactions → Extract & Analyze):

Step	What happens	Component
1. Build Panel	Define your market, generate diverse personas	Panel Builder
2. Run Ask / Concept Test	Each persona responds independently in its own subprocess	Simulation Engine
3. Review Findings	Structured report with themes, cross-tabs, charts, and verbatims	Analysis Pipeline

Recommended workflow:

/persona generate — build a reusable panel
/persona ask — explore motivations, barriers, language, and decision criteria
/persona concept-test — compare explicit options when ready for a structured choice task

Quality Guidelines

Take your time with persona generation. Diverse, detailed personas are the foundation of useful results. Do not skip diversity verification.
Do not skip validation. Always verify response JSON structure before proceeding to analysis.
Quality over speed. A 5-persona panel with rich, differentiated responses is more valuable than a 15-persona panel with generic answers.

Quick Reference

Command	What it does
`/persona generate Running shoe shoppers in the US`	Build a reusable panel (default 5 personas)
`/persona generate --count 10 Gen Z skincare shoppers in the US`	Panel with custom size
`/persona generate --segments Canned coffee drinkers in Japan`	Segment-driven panel (default 15)
`/persona ask What frustrates you most about choosing skincare products?`	Explore motivations and barriers
`/persona ask Why would you ignore an ad for a new running shoe?`	Qualitative reaction before concept test
`/persona concept-test Compare 3 running shoe concepts`	Concept test — concepts provided interactively
`/persona concept-test --market japan Evaluate 3 canned coffee concepts`	Concept test with Japanese panel

Read the full file on GitHub · 675 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 675 lines · 104 tokens per session scan A fbc741012554

Subscribe to this mod's changes

persona is a skill published in the GitHub repository takechanman1228/claude-persona (60 stars, last pushed 4mo ago), licensed MIT. It adds 104 tokens to every session and 7,210 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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persona next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
personatakechanman1228/claude-persona	Skill	60	4mo ago	MIT	A	104	Claude Code
ecomtakechanman1228/claude-ecom	Skill	54	4mo ago	MIT	A	74	Claude Code
html-ppt-zhangzara-coralnexu-io/open-design	Skill	106k	yesterday	Apache-2.0	A	55	Claude Code, Codex
adscoreyhaines31/marketingskills	Skill	59k	2d ago	MIT	A	239	Claude Code
co-marketingcoreyhaines31/marketingskills	Skill	59k	2d ago	MIT	A	92	Claude Code
press-media-relationsaaron-he-zhu/aaron-marketing-skills	Skill	3.1k	yesterday	Apache-2.0	A	150	Claude Code
share-of-voice-trackeraaron-he-zhu/aaron-marketing-skills	Skill	3.1k	yesterday	Apache-2.0	A	184	Claude Code