saas-replacement-planner

saas-replacement-planner is a skill for Claude Code, Codex from OneWave-AI/claude-skills. It costs 68 tokens per session (653 once invoked), scanned A, original, MIT.

A planning guide for deciding which subscription software a company might replace with AI agents. It compares replacement feasibility, subscription costs, development costs, risks, integrations, and compliance needs.

In plain words
What is it for?
Reviewing a software stack, comparing build-versus-buy options, prioritizing replacement candidates, and estimating potential savings and implementation effort.
Why use it?
It helps companies judge whether building an AI-based alternative is financially and operationally sensible instead of assuming every tool can be replaced.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: model in frontmatter.

Good fit Reviewing a software stack, comparing build-versus-buy options, prioritizing replacement candidates, and estimating potential savings and implementation effort.

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Install with agentmods
npx agentmods add skills/onewave-ai/claude-skills/saas-replacement-planner
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 OneWave-AI/claude-skills --skill saas-replacement-planner
Clone the repo
git clone --depth 1 https://github.com/OneWave-AI/claude-skills

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 saas-replacement-planner

README.md
[![agentmods](https://agentmods.dev/badge/skills/onewave-ai/claude-skills/saas-replacement-planner/github.svg)](https://agentmods.dev/skills/onewave-ai/claude-skills/saas-replacement-planner)
Your own site
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/saas-replacement-planner"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/saas-replacement-planner/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 saas-replacement-planner

Your own site · 80×15
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/saas-replacement-planner"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/saas-replacement-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 653 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 $0.00068 $0.00653
Opus 5 $0.00034 $0.00327
Sonnet 5 $0.00014 $0.00131
Haiku 4.5 $0.00007 $0.00065

Measured 9d ago against content hash ffa9a46345d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

saas-replacement-planner 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 9d 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.

saas-replacement-planner/SKILL.md · 32 lines

How it starts

The opening of the file, as written. The whole thing — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.
  2. Research current pricing. For each tool, verify pricing with WebSearch when numbers are missing or look off. Check per-seat pricing, outdated plans, API access for the replacement, and data export capability.
  3. Analyze each tool. Run the complete six-step framework in references/analysis-framework.md for every tool. Do not skip tools or give superficial analysis. Apply matching patterns from references/patterns.md.
  4. Build the priority matrix. Plot all tools on the Impact vs Effort axes. Sequence replacements and group tools that share infrastructure (e.g., all needing Supabase) to reduce incremental build cost.
  5. Generate the timeline. Create a realistic timeline accounting for engineering capacity, parallel running periods, dependencies between replacements, and quick wins that fund later investments.
  6. Write the plan. Generate saas-replacement-plan.md in the current working directory using the structure in references/output-template.md. Follow the rigor and quality standards in references/analysis-guidelines.md.
  7. Present key findings. After writing the file, summarize total potential savings, the top 3 quick wins, any surprising findings, and the recommended first action.

Read the full file on GitHub · 32 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 32 lines · 68 tokens per session scan A ffa9a46345d7

Subscribe to this mod's changes

saas-replacement-planner is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 653 once invoked, about $0.0003 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 2026-09-03.

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