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Install in OpenClaw
/install afrexai-pricing-optimizer
Description
Analyzes and optimizes pricing strategy using proven frameworks
README (SKILL.md)
Pricing Optimizer
You optimize pricing strategy like a pricing consultant. Data-driven, psychology-informed, revenue-maximizing.
Process
1. Discovery
Ask about:
- Current pricing (tiers, amounts, billing frequency)
- Target customer (B2B/B2C, segment, budget range)
- Competitors and their pricing
- Current conversion rates and churn
- Cost structure (COGS, CAC, margins)
- Value metrics (what drives customer value?)
2. Analysis Frameworks
Value-Based Pricing:
- What's the customer's next best alternative?
- What's the economic value your product creates?
- Price should be between cost and value created
Competitive Positioning:
- Map competitors on price vs. feature matrix
- Identify pricing gaps and opportunities
- Determine if you're premium, mid-market, or budget
Psychology:
- Anchoring (show expensive tier first)
- Charm pricing ($47 vs $50)
- Decoy effect (3-tier with obvious "best value")
- Annual discount (lock-in + cash flow)
3. Output
## Pricing Analysis: [Product]
### Current State
- Revenue: ...
- Conversion: ...
- ARPU: ...
### Recommended Pricing
| Tier | Price | Target | Key Features |
|------|-------|--------|-------------|
| ... | ... | ... | ... |
### Expected Impact
- Revenue change: +X%
- Conversion change: ...
- ARPU change: ...
### Implementation Plan
1. ...
### A/B Test Suggestions
- ...
Rules
- Always consider willingness-to-pay, not just cost-plus
- Recommend A/B testing before full rollout
- Consider annual vs monthly trade-offs
- Flag if current pricing leaves money on the table
Related Tools
- Revenue calculator: https://afrexai-cto.github.io/ai-revenue-calculator/
- Lead scoring:
clawhub install afrexai-lead-scorer - Industry context: https://afrexai-cto.github.io/context-packs/ ($47/pack)
Usage Guidance
This skill appears coherent and limited to pricing advice, but exercise normal caution before following external links or running the suggested `clawhub install` command. Do not paste sensitive customer PII, API keys, or proprietary data into the skill. Verify the trustworthiness of the referenced afrexai-cto.github.io pages and any paid 'context packs' before paying. If you plan to install or use the referenced 'afrexai-lead-scorer' skill, review its install/source and permissions separately. If you need higher assurance, ask the publisher for a homepage or source repository to inspect before using in production.
Capability Analysis
Type: OpenClaw Skill
Name: afrexai-pricing-optimizer
Version: 1.0.0
The OpenClaw AgentSkills bundle 'afrexai-pricing-optimizer' is benign. The `SKILL.md` file provides instructions for an AI agent to act as a pricing consultant, outlining a process for discovery, analysis, and output. It includes references to external URLs for related tools (GitHub Pages links) and a `clawhub install` command for another skill, which are standard ways to link resources or extend functionality within the OpenClaw ecosystem. There is no evidence of prompt injection with malicious intent, data exfiltration, unauthorized command execution, persistence mechanisms, or obfuscation.
Capability Assessment
Purpose & Capability
Name and description match the content of SKILL.md: discovery questions, pricing frameworks, outputs and A/B test suggestions. The skill does not declare any unrelated binaries, env vars, or config paths.
Instruction Scope
Runtime instructions stay within pricing analysis scope and do not instruct reading files, env vars, or system state. The SKILL.md references external resources (two afrexai-cto.github.io links) and suggests running `clawhub install afrexai-lead-scorer` and paid 'context packs' ($47/pack); those are external referrals that could lead to network activity, installs, or purchases if the user follows them, but the skill itself does not perform those actions.
Install Mechanism
No install spec and no code files — instruction-only. Nothing is written to disk by the skill as provided.
Credentials
No environment variables, credentials, or config paths are requested. This is proportionate for a consultant-style pricing tool.
Persistence & Privilege
Skill is not forced-always and does not request system configuration or cross-skill modifications. Default autonomous invocation is allowed but is normal for skills and not by itself risky here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install afrexai-pricing-optimizer - After installation, invoke the skill by name or use
/afrexai-pricing-optimizer - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Pricing Optimizer skill.
- Provides a step-by-step framework for analyzing and optimizing pricing strategies.
- Incorporates value-based, competitive, and psychological pricing principles.
- Includes templates for pricing analysis, recommendations, and A/B testing.
- Lists related tools and best practices for maximizing revenue.
Metadata
Frequently Asked Questions
What is AfrexAI Pricing Optimizer?
Analyzes and optimizes pricing strategy using proven frameworks. It is an AI Agent Skill for Claude Code / OpenClaw, with 831 downloads so far.
How do I install AfrexAI Pricing Optimizer?
Run "/install afrexai-pricing-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is AfrexAI Pricing Optimizer free?
Yes, AfrexAI Pricing Optimizer is completely free (open-source). You can download, install and use it at no cost.
Which platforms does AfrexAI Pricing Optimizer support?
AfrexAI Pricing Optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created AfrexAI Pricing Optimizer?
It is built and maintained by 1kalin (@1kalin); the current version is v1.0.0.
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