creating-superfans-hodak

creating-superfans-hodak is a skill for Claude Code, Codex from simbajigege/book2skills. It costs 34 tokens per session (1,864 once invoked), scanned A, original, MIT.

A customer-experience planning skill based on Brittany Hodak’s SUPER Model for building customer loyalty and referrals.

In plain words
What is it for?
It is for work involving customer understanding, loyalty, word of mouth, referrals, personalisation, service recovery, and customer-experience operations.
Why use it?
It helps teams understand customers, personalise experiences, recover from service problems, and create repeatable advocacy practices.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for work involving customer understanding, loyalty, word of mouth, referrals, personalisation, service recovery, and customer-experience operations.

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Install with agentmods
npx agentmods add skills/simbajigege/book2skills/creating-superfans-hodak
Install

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.

Any agent
npx skills add simbajigege/book2skills --skill creating-superfans-hodak
Clone the repo
git clone --depth 1 https://github.com/simbajigege/book2skills

Made for: Claude Code, Codex.

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.

agentmods badge for creating-superfans-hodak

README.md
[![agentmods](https://agentmods.dev/badge/skills/simbajigege/book2skills/creating-superfans-hodak/github.svg)](https://agentmods.dev/skills/simbajigege/book2skills/creating-superfans-hodak)
Your own site
<a href="https://agentmods.dev/skills/simbajigege/book2skills/creating-superfans-hodak"><img src="https://agentmods.dev/badge/skills/simbajigege/book2skills/creating-superfans-hodak/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.

agentmods 80×15 button for creating-superfans-hodak

Your own site · 80×15
<a href="https://agentmods.dev/skills/simbajigege/book2skills/creating-superfans-hodak"><img src="https://agentmods.dev/badge/skills/simbajigege/book2skills/creating-superfans-hodak.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,864 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00034 $0.01864
Opus 5 $0.00017 $0.00932
Sonnet 5 $0.00007 $0.00373
Haiku 4.5 $0.00003 $0.00186

Measured 12d ago against content hash 755ea0ba13d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

creating-superfans-hodak 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 12d 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/creating-superfans-hodak/SKILL.md · 160 lines

How it starts

The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Creating Superfans - Skill (Brittany Hodak)

Knowledge source: Creating Superfans: Turning Everyday Customers into Enthusiastic Advocates by Brittany Hodak, 2023. Architecture: Orchestrator + 7 subskills. This file routes the user query; subskills execute the actual workflows.

creating-superfans-hodak/
├── SKILL.md
└── subskills/
    ├── m1_superfan_diagnosis/
    │   ├── module.md
    │   └── references/case_library.md
    ├── m2_story_positioning/
    │   ├── module.md
    │   └── references/case_library.md
    ├── m3_customer_understanding/
    │   ├── module.md
    │   └── references/case_library.md
    ├── m4_personalization/
    │   ├── module.md
    │   └── references/case_library.md
    ├── m5_exceed_expectations/
    │   ├── module.md
    │   └── references/case_library.md
    ├── m6_service_recovery/
    │   ├── module.md
    │   └── references/case_library.md
    └── m7_repeatable_supergroups/
        ├── module.md
        └── references/case_library.md

Skill Purpose

Help founders, marketers, sales teams, customer success leaders, support teams, and operators turn ordinary customers into enthusiastic advocates. Hodak's core idea is that superfans are created where the brand's story intersects with the customer's story, then reinforced through understanding, personalization, expectation-exceeding experiences, recovery, and repeatable systems.

This is not a paid ads, SEO, pricing, funnel analytics, or generic growth-hacking playbook. Use it when the question involves customer experience, loyalty, retention, referrals, reviews, advocacy, service recovery, or cross-functional customer centricity.

Workflow Inventory

Workflow User question pattern Inputs Output Subskill
Superfan diagnosis "Why are customers not coming back or referring?" Customer segment, current journey, retention/referral symptoms Ladder stage, apathy diagnosis, weak SUPER pillar M1
Story positioning "How do we differentiate without lowering price?" Brand origin, values, market, customer promise Story intersection and category-of-one positioning M2
Customer understanding "Who are our customers and what do they really want?" Customer type, conversations, reviews, support notes Customer STORY map and voice-of-customer questions M3
Personalization "How do we make customers feel seen?" Customer signals, CRM fields, journey stage, boundaries Personalization actions and triggers M4
Exceed expectations "How do we create word of mouth or memorable experiences?" Journey touchpoints, expectations, emotional moments Repeatable experience moments and advocacy triggers M5
Service recovery "A customer had a bad experience. What should we do?" Failure details, customer impact, relationship context 5 As recovery plan and prevention fix M6
Repeatable supergroups "How do we scale CX across teams?" Team structure, processes, feedback loops, employee experience System, ownership, metrics, and cross-functional rollout M7

Read the full file on GitHub · 160 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.

  1. 12d ago First seen · 160 lines · 34 tokens per session scan A 755ea0ba13d9

Subscribe to this mod's changes

creating-superfans-hodak is a skill published in the GitHub repository simbajigege/book2skills (163 stars, last pushed 17d ago), licensed MIT. It adds 34 tokens to every session and 1,864 once invoked, about $0.0002 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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