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 reatlat/fullstory-claude-plugin --skill persona-buildergit clone --depth 1 https://github.com/reatlat/fullstory-claude-pluginWrote 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/reatlat/fullstory-claude-plugin/persona-builder)<a href="https://agentmods.dev/skills/reatlat/fullstory-claude-plugin/persona-builder"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/persona-builder/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/reatlat/fullstory-claude-plugin/persona-builder"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/persona-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.01376 |
| Opus 5 | $0.00026 | $0.00688 |
| Sonnet 5 | $0.00010 | $0.00275 |
| Haiku 4.5 | $0.00005 | $0.00138 |
Grade A, and why
persona-builder 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 11d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona Builder
Build behavioral personas from real session data — identify who your users actually are based on what they do, not what you assume.
When to Use
- "What types of users do we have?"
- "Build personas for the product team"
- "Who are our power users vs casual users?"
- "What's the difference between users who convert and users who don't?"
- "Define our ideal customer profile from behavioral data"
Mental Model
Traditional personas are built from interviews and assumptions. Behavioral personas are built from what users actually do. The difference matters:
- "Sarah the Marketing Manager, 34, Chicago" — traditional persona (demographic)
- "The Power Browser: visits 3+ times/week, compares products extensively, reads reviews, converts on 4th visit" — behavioral persona (what matters for product decisions)
Workflow
Step 1: Discover behavioral clusters
Run broad metrics to find natural grouping dimensions:
fullstory:build_metric(query="sessions per user in last 30 days", output_type="top_n")
fullstory:build_metric(query="pages per session", output_type="top_n")
fullstory:build_metric(query="time on site per session", output_type="top_n")
fullstory:build_metric(query="features used per user", output_type="top_n")
Look for natural breakpoints:
- Session count: 1 (one-and-done), 2-5 (occasional), 6-20 (regular), 20+ (power)
- Pages per session: 1-2 (bouncers), 3-5 (browsers), 6+ (deep explorers)
- Features: 1-2 (single-purpose), 3-5 (multi-feature), 6+ (power user)
Step 2: Build segments for each cluster
fullstory:build_segment("users with 20+ sessions in last 30 days") → power_users
fullstory:build_segment("users with 1 session in last 30 days") → one_timers
fullstory:build_segment("users with 2-5 sessions, 3-5 pages per session") → casual_browsers
Step 3: Profile each persona
For each segment, pull sessions and analyze:
fullstory:get_sessions(segment_id, limit=10)
→ session-context: "What is this user's typical flow? What features do they use? What frustrates them? What do they achieve?"
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.
- 11d ago First seen · 130 lines · 52 tokens per session scan A 03a11fa170b0
persona-builder is a skill published in the GitHub repository reatlat/fullstory-claude-plugin (62 stars, last pushed 29d ago), licensed MIT. It adds 52 tokens to every session and 1,376 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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