Pricing Strategy
v1.0.0When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,'...
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byMario Karras@mariokarras
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name and description (pricing strategy, tiers, research methods) match the SKILL.md content and the two reference docs. The skill requests no binaries, env vars, or external credentials — which is appropriate for an advisory, instruction-only skill.
Instruction Scope
Instructions are narrowly focused on pricing frameworks, research methods, tiering, and communication strategies. The only operational behavior called out is: 'If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md), read it first.' That is reasonable for context-aware recommendations, but it does require the agent to read a local workspace file if present. There's no instruction to read arbitrary system files, access network endpoints, or exfiltrate data.
Install Mechanism
This is an instruction-only skill with no install spec and no code to write to disk. That minimizes installation risk.
Credentials
The skill requests no environment variables, credentials, or config paths. Its data needs (product marketing context, conversion metrics, ARPU, etc.) are reasonable and relevant to pricing advice.
Persistence & Privilege
always is false and the skill is user-invocable. It does not request permanent presence or modify other skills. The agent may invoke it autonomously (platform default), which is expected for skills of this type.
Assessment
This skill appears internally consistent and low-risk: it’s an instruction-only pricing advisor, requests no credentials, and installs nothing. Two practical cautions before enabling it: (1) it explicitly tells the agent to read .agents/product-marketing-context.md (or .claude/...), so inspect that file for any secrets or sensitive information before placing it in the agent workspace; if you don’t want the skill to read local files, remove or sanitize that file. (2) although autonomous invocation is the platform default and fine here, consider whether you want the agent to call advisory skills automatically; if not, restrict invocation or require explicit user prompts. If you want extra assurance, test the skill in a sandboxed workspace with non-sensitive sample data first.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.