Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nicepkg/ai-workflow --skill buyer-persona-generatorgit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote 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.
[](https://agentmods.dev/skills/nicepkg/ai-workflow/buyer-persona-generator)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/buyer-persona-generator"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/buyer-persona-generator/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.
<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/buyer-persona-generator"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/buyer-persona-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00060 | $0.02366 |
| Opus 5 | $0.00030 | $0.01183 |
| Sonnet 5 | $0.00012 | $0.00473 |
| Haiku 4.5 | $0.00006 | $0.00237 |
Grade A, and why
buyer-persona-generator 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Buyer Persona Generator
Create data-driven buyer personas and Ideal Customer Profiles (ICP) for targeted marketing.
When to Use
- Launching a new product or service
- Entering new markets or segments
- Refining marketing messaging
- Training sales teams
- Creating targeted content
- Improving ad targeting
Persona Types
B2B Personas
- Economic Buyer - Signs the contract, cares about ROI
- Technical Buyer - Evaluates product fit, cares about specs
- User/Champion - Daily user, advocates internally
- Blocker - Potential objector, needs addressing
B2C Personas
- Primary User - Main customer segment
- Secondary User - Adjacent segment
- Influencer - Affects purchase decision
- Decision Maker - Makes final purchase
Output Format
B2B Buyer Persona
═══════════════════════════════════════════════════════════════
BUYER PERSONA: [Persona Name]
═══════════════════════════════════════════════════════════════
PERSONA SNAPSHOT
─────────────────────────────────────────────────────────────
Name: "[Fictional Name]"
Role: [Job Title]
Type: [Economic Buyer / Technical Buyer / Champion / Blocker]
Priority: [Primary / Secondary / Tertiary]
DEMOGRAPHICS
─────────────────────────────────────────────────────────────
Job Title: [Specific titles]
Department: [Marketing, Engineering, Operations, etc.]
Seniority: [C-level, VP, Director, Manager, IC]
Reports To: [Who they report to]
Team Size: [Direct reports]
Company Size: [Employee count range]
Industry: [Vertical/sector]
Location: [Geography]
Age Range: [Typical age]
Income: [Salary range]
Education: [Typical background]
PSYCHOGRAPHICS
─────────────────────────────────────────────────────────────
Personality Type: [Analytical / Driver / Amiable / Expressive]
Decision Style: [Data-driven / Gut-feel / Consensus / Decisive]
Risk Tolerance: [Low / Medium / High]
Tech Savviness: [Early adopter / Mainstream / Laggard]
Information Sources:
- [Where they learn: podcasts, newsletters, conferences]
- [Who they follow: influencers, publications]
- [Communities: LinkedIn groups, Slack, forums]
GOALS & MOTIVATIONS
─────────────────────────────────────────────────────────────
Professional Goals:
1. [Primary goal - what they're measured on]
2. [Secondary goal]
3. [Career aspiration]
Personal Motivations:
1. [What drives them personally]
2. [Status, security, growth, etc.]
Success Metrics (KPIs):
- [What metrics define their success]
- [How they're evaluated]
PAIN POINTS & CHALLENGES
─────────────────────────────────────────────────────────────
Top Frustrations:
1. [Biggest daily pain] - Severity: High
2. [Second pain point] - Severity: Medium
3. [Third pain point] - Severity: Medium
Current Solutions:
- [What they use today]
- [Workarounds they've created]
- [Why current solutions fall short]
Triggers for Change:
- [Events that make them seek solutions]
- [Budget cycle timing]
- [Organizational changes]
BUYING BEHAVIOR
─────────────────────────────────────────────────────────────
Role in Purchase: [Decision Maker / Influencer / User / Blocker]
Budget Authority: [Yes/No, up to $X]
Research Process:
1. [How they discover solutions]
2. [What they evaluate]
3. [Who they consult]
Evaluation Criteria (ranked):
1. [Most important factor]
2. [Second factor]
3. [Third factor]
4. [Fourth factor]
5. [Fifth factor]
Sales Cycle Stage: [Aware / Considering / Evaluating / Deciding]
Preferred Contact: [Email / Phone / LinkedIn / In-person]
Content Preferences: [Case studies / Demos / Whitepapers / Webinars]
OBJECTIONS & CONCERNS
─────────────────────────────────────────────────────────────
Common Objections:
1. "[Objection]"
→ Response: [How to address]
2. "[Objection]"
→ Response: [How to address]
3. "[Objection]"
→ Response: [How to address]
Fears:
- [What keeps them up at night about this decision]
- [Career risk concerns]
- [Implementation worries]
MESSAGING STRATEGY
─────────────────────────────────────────────────────────────
Value Proposition for This Persona:
"[One sentence tailored to their needs]"
Key Messages (prioritized):
1. [Most resonant message]
2. [Second message]
3. [Third message]
Proof Points:
- [Specific evidence that convinces them]
- [Case study type they'd want]
- [Stats/data that matter]
Tone: [Professional / Technical / Friendly / Authoritative]
CONTENT MAP
─────────────────────────────────────────────────────────────
Awareness Stage:
- [Blog post topics]
- [Educational content]
Consideration Stage:
- [Comparison guides]
- [Webinars]
Decision Stage:
- [Case studies]
- [ROI calculator]
- [Demo]
QUOTES (What They Say)
─────────────────────────────────────────────────────────────
"[Direct quote expressing a pain point]"
"[Quote about what they want]"
"[Quote about their concerns]"
A DAY IN THEIR LIFE
─────────────────────────────────────────────────────────────
Morning: [What they do]
Midday: [Meetings, tasks]
Afternoon: [Priorities]
Challenges: [What frustrates them daily]
Wins: [What makes a good day]
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.
- 9d ago First seen · 355 lines · 60 tokens per session scan A bce490a2a955
buyer-persona-generator is a skill published in the GitHub repository nicepkg/ai-workflow (282 stars, last pushed 7mo ago), licensed MIT. It adds 60 tokens to every session and 2,366 once invoked, about $0.0003 per session on Opus 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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