Individual skill
saas-replacement-planner
Evaluates which SaaS tools can be replaced with AI agents. Takes a list of current SaaS subscriptions with costs, assesses replacement feasibility, estimates build vs buy economics, identifies Claude+MCP alternatives, and generates a comprehensive replacement plan with priority matrix, ROI analysis, implementation timeline, and risk assessment.
saas-replacement-planner/SKILL.md
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- Last checked
- Nov 10, 2026
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- Repository last updated
- Oct 20, 2026
- License
- MIT
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- agent-skills Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- developer-tools Repository topic
- llm Repository topic
- prompt-engineering Repository topic
- sales-automation Repository topic
- engineering Derived category
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SKILL.mdcore · 3,258 bytesreferences/analysis-framework.mddoc · 6,738 bytesreferences/analysis-guidelines.mddoc · 2,666 bytesreferences/output-template.mddoc · 5,377 bytesreferences/patterns.mddoc · 3,956 bytes
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# SaaS Replacement Planner
Evaluate a company's SaaS stack and produce a rigorous, actionable plan that quantifies the ROI of migrating from subscription software to AI-agent-powered alternatives. Bias toward replacement where the economics support it, but stay honest: not every tool can be replaced today.
## Contents
- `references/analysis-framework.md` -- the six-step per-tool analysis (classification, feasibility tiers, build-cost formulas, Claude+MCP architecture, risk scoring, priority matrix)
- `references/output-template.md` -- full `saas-replacement-plan.md` document structure
- `references/patterns.md` -- proven replacement patterns by category and edge-case handling
- `references/analysis-guidelines.md` -- estimation rigor, honesty rules, OneWave AI thesis, and output quality standards
## Workflow
1. **Gather input.** Collect the SaaS tool list. Parse screenshots, CSVs, or bank statements; organize informal lists into a structured format (tool, monthly/annual cost, seats, primary use case). Ask clarifying questions only when critical data is missing: seat counts, primary workflows, integration dependencies, mission-critical vs nice-to-have, and compliance requirements.