decision-moment-skill
Map and optimize decision moments across Awareness, Consideration, Conversion, and Retention, then attach specific assets, visuals, and automations to each stage. Use when designing funnels, campaigns, or retention systems.
Best use case
decision-moment-skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Map and optimize decision moments across Awareness, Consideration, Conversion, and Retention, then attach specific assets, visuals, and automations to each stage. Use when designing funnels, campaigns, or retention systems.
Map and optimize decision moments across Awareness, Consideration, Conversion, and Retention, then attach specific assets, visuals, and automations to each stage. Use when designing funnels, campaigns, or retention systems.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "decision-moment-skill" skill to help with this workflow task. Context: Map and optimize decision moments across Awareness, Consideration, Conversion, and Retention, then attach specific assets, visuals, and automations to each stage. Use when designing funnels, campaigns, or retention systems.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/decision-moment-skill/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How decision-moment-skill Compares
| Feature / Agent | decision-moment-skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Map and optimize decision moments across Awareness, Consideration, Conversion, and Retention, then attach specific assets, visuals, and automations to each stage. Use when designing funnels, campaigns, or retention systems.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Decision Moment Skill
## Purpose
Turn raw offers and services into structured decision-moment maps that tell us exactly:
- **Where** a prospect is in their journey
- **What** they need to see/feel/understand next
- **Which** asset (page, email, video, social post) should be delivered
## Outputs
For each client/campaign:
1. **Journey Map**
- Awareness → Problem Aware → Solution Aware → Provider Aware → Purchase → Retention
2. **Decision Moments**
- Each moment contains:
- Problem statement
- Blocking objection(s)
- Required proof
- Recommended asset type
- Link to asset in `social_assets` or page route
3. **Execution Map**
- Which channel carries which moment (email, ad, social, landing page)
## Data Structures (DB)
- `decision_moment_maps` table to hold the overall map
- `decision_assets` table to join moments to specific assets
## When to Use
- After Social Playbook creation
- When designing onboarding journeys
- When improving conversion on an existing flow
## Constraints
- Always align with the No-Bluff protocol and verified value propositions.
## Decision Moment Framework
### Stage 1: Awareness
- "I have a problem but don't know what to call it"
- Asset types: Educational content, social posts, blog articles
- Goal: Get attention, define the problem
### Stage 2: Consideration
- "I know the problem, exploring solutions"
- Asset types: Comparison guides, case studies, how-to videos
- Goal: Position as the best solution
### Stage 3: Conversion
- "Ready to buy, need final push"
- Asset types: Demos, trials, testimonials, pricing pages
- Goal: Remove final objections, close deal
### Stage 4: Retention
- "Customer, keep them happy and growing"
- Asset types: Onboarding, tutorials, upsells, check-ins
- Goal: Maximize lifetime valueRelated Skills
architecture-decision-records
Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
clinical-decision-support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
decisions
Load past architectural decisions. Use when making new decisions to ensure consistency.
technical-decision-record
Use when making technical decisions, choosing technologies, or documenting architectural choices. Creates ADRs (Architecture Decision Records).
decision-action
Use when the user needs to choose, prioritize, or make a go/no-go decision among options.
architecture-decision-record
Use this skill when documenting significant architectural decisions. Provides ADR templates following the Nygard format with sections for context, decision, consequences, and alternatives. Helps teams maintain architectural memory and rationale for backend systems, API designs, database choices, and infrastructure decisions.
azure-quotas
Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".
raindrop-io
Manage Raindrop.io bookmarks with AI assistance. Save and organize bookmarks, search your collection, manage reading lists, and organize research materials. Use when working with bookmarks, web research, reading lists, or when user mentions Raindrop.io.
zlibrary-to-notebooklm
自动从 Z-Library 下载书籍并上传到 Google NotebookLM。支持 PDF/EPUB 格式，自动转换，一键创建知识库。
discover-skills
当你发现当前可用的技能都不够合适（或用户明确要求你寻找技能）时使用。本技能会基于任务目标和约束，给出一份精简的候选技能清单，帮助你选出最适配当前任务的技能。
web-performance-seo
Fix PageSpeed Insights/Lighthouse accessibility "!" errors caused by contrast audit failures (CSS filters, OKLCH/OKLAB, low opacity, gradient text, image backgrounds). Use for accessibility-driven SEO/performance debugging and remediation.
project-to-obsidian
将代码项目转换为 Obsidian 知识库。当用户提到 obsidian、项目文档、知识库、分析项目、转换项目 时激活。 【激活后必须执行】： 1. 先完整阅读本 SKILL.md 文件 2. 理解 AI 写入规则（默认到 00_Inbox/AI/、追加式、统一 Schema） 3. 执行 STEP 0: 使用 AskUserQuestion 询问用户确认 4. 用户确认后才开始 STEP 1 项目扫描 5. 严格按 STEP 0 → 1 → 2 → 3 → 4 顺序执行 【禁止行为】： - 禁止不读 SKILL.md 就开始分析项目 - 禁止跳过 STEP 0 用户确认 - 禁止直接在 30_Resources 创建（先到 00_Inbox/AI/） - 禁止自作主张决定输出位置