Amazon Buy Box Monitor
browser-act/skills
Pulls Amazon product details, competing seller prices and seller ratings for a given ASIN through the BrowserAct API, without browser automation.
Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data.
Install Rfm Customer Segmentation
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main rfm-customer-segmentation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/liangdabiao/claude-data-analysis-ultra-main.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/rfm-customer-segmentation .claude/skills/rfm-customer-segmentation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "rfm-customer-segmentation" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentation into .claude/skills/rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rfm-customer-segmentation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main rfm-customer-segmentation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/claude-data-analysis-ultra-main.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/rfm-customer-segmentation .agents/skills/rfm-customer-segmentation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "rfm-customer-segmentation" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentation into .agents/skills/rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rfm-customer-segmentation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main rfm-customer-segmentation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/claude-data-analysis-ultra-main.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/rfm-customer-segmentation .cursor/skills/rfm-customer-segmentation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "rfm-customer-segmentation" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentation into .cursor/skills/rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rfm-customer-segmentation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/liangdabiao/claude-data-analysis-ultra-main.git --path .claude/skills/rfm-customer-segmentation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main rfm-customer-segmentation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/claude-data-analysis-ultra-main.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/rfm-customer-segmentation .gemini/skills/rfm-customer-segmentation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "rfm-customer-segmentation" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentation into .gemini/skills/rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rfm-customer-segmentation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main rfm-customer-segmentationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/liangdabiao/claude-data-analysis-ultra-main.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/rfm-customer-segmentation .github/skills/rfm-customer-segmentation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "rfm-customer-segmentation" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentation into .github/skills/rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rfm-customer-segmentation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main rfm-customer-segmentation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/claude-data-analysis-ultra-main.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/rfm-customer-segmentation .opencode/skills/rfm-customer-segmentation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "rfm-customer-segmentation" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/rfm-customer-segmentation into .opencode/skills/rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rfm-customer-segmentation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
rfm-customer-segmentation- GitHub stars
- 290
- Token cost
- ~1k tokens
- SKILL.md length
- 392 words
- Files
- 11
- Skills in repo
- 19
- Repo updated
- First seen
- Licence
- None found
At a glance
Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data.
- Works in 4 steps: Data Analysis → Customer Segmentation → Visualization and Reporting → …
- You need to analyze customer value
- SKILL.md covers Instructions, Usage Examples, Key Features and File Requirements, plus 3 more sections
- Runs Python scripts from its folder
What it does
Rfm Customer Segmentation is an agent skill from liangdabiao/claude-data-analysis-ultra-main. Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data. Use when you need to analyze customer value, identify VIP customers, or create marketing segments. Automatically cleans data, calculates RFM metrics, applies K-means clustering, and generates visualization reports with Chinese language support.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files (for example `README.md`, `core_analysis.py` and `examples/basic_usage.md`).
It sits in Sales & Support, covering E-commerce operations. The repository describes itself as: 让小白都可以一键进行数据分析，搞互联网的，搞电商的，搞各种各样的，那么其实就会用到 互联网的数据分析， 例如互联网会关心 拉新，留存，促活，推荐，转化，A/B test, 用户分析 等等很多有用的数据分析。
When your agent uses it
- You need to analyze customer value
- Identify VIP customers
- Create marketing segments
Example prompts
- “/rfm-customer-segmentation”
Requirements
- Python 3
- Pre-approved tools (allowed-tools): Read, Write, Bash, Glob
Workflow steps
4 steps, taken from the step headings in SKILL.md.
- Data Analysis
- Customer Segmentation
- Visualization and Reporting
- Marketing Insights
What it can do on your machine
Read from SKILL.md and the folder at commit 6b52856. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteBashGlob
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Rfm Customer Segmentation loads about 1k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 392 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Write, Bash, Glob
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 392 words (~1,030 tokens).
“A comprehensive customer segmentation skill that automatically analyzes e-commerce transaction data to identify customer value segments using RFM (Recency, Frequency, Monetary) analysis with K-means clustering.”
- name
- rfm-customer-segmentation
- allowed-tools
- Read, Write, Bash, Glob
Files
SKILL.md and 10 other files in .claude/skills/rfm-customer-segmentation of liangdabiao/claude-data-analysis-ultra-main.
- SKILL.md
- README.md
- core_analysis.py
- examples/basic_usage.md
- examples/sample_data.csv
- report_generator.py
- requirements.txt
- simple_rfm.py
- templates/analysis_template.md
- templates/vip_list_template.csv
- visualization.py
Open the folder on GitHubat commit 6b52856
Compare with similar skills
Rfm Customer Segmentation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Rfm Customer Segmentation this skillliangdabiao/claude-data-analysis-ultra-main | 290 | — | ~1k | Automated safety check: Notes | None | |
| Amazon Buy Box Monitorbrowser-act/skills | 6.1k | 1 repos | ~1.6k | Automated safety check: Pass | MIT | |
| Tourmind Bookingtourmind-com/Tourmind-Booking-Skills | 1.8k | — | ~13k | Automated safety check: Pass | MIT | |
| Ecommerce Image Suitewzj177/ecommerce-image-suite | 449 | — | ~10k | Automated safety check: Pass | Apache-2.0 | |
| Zach Feature Demand Validatorzach22-1999/amazon-skills | 209 | 1 repos | ~2.3k | Automated safety check: Notes | MIT | |
| Caramel CouponsDevinoSolutions/caramel | 141 | — | ~1.1k | Automated safety check: Pass | AGPL-3.0 |
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Related
Categories
Questions about Rfm Customer Segmentation
What does Rfm Customer Segmentation do?
Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data. Rfm Customer Segmentation is an agent skill from liangdabiao/claude-data-analysis-ultra-main. Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data.
When should I use Rfm Customer Segmentation?
Rfm Customer Segmentation fits situations like: you need to analyze customer value; identify VIP customers; create marketing segments.
How do I install Rfm Customer Segmentation in Claude Code?
Run `npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a claude-code`. Or copy the skill folder (.claude/skills/rfm-customer-segmentation in liangdabiao/claude-data-analysis-ultra-main) into .claude/skills/rfm-customer-segmentation in your project. Claude Code loads it when a task matches its description.
How do I install Rfm Customer Segmentation in Codex?
Run `npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a codex`. Or copy the skill folder (.claude/skills/rfm-customer-segmentation in liangdabiao/claude-data-analysis-ultra-main) into .agents/skills/rfm-customer-segmentation in your project. Codex loads it when a task matches its description.
Can I use Rfm Customer Segmentation in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add liangdabiao/claude-data-analysis-ultra-main --skill rfm-customer-segmentation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rfm-customer-segmentation, .gemini/skills/rfm-customer-segmentation, .github/skills/rfm-customer-segmentation and .opencode/skills/rfm-customer-segmentation in your project.
What does Rfm Customer Segmentation need to run?
Going by SKILL.md and its folder, Rfm Customer Segmentation needs Python for the scripts in its folder. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Bash, Glob.
Does Rfm Customer Segmentation access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Rfm Customer Segmentation safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Rfm Customer Segmentation use?
No licence was found for Rfm Customer Segmentation or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Rfm Customer Segmentation use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Rfm Customer Segmentation?
Skills that share tags, products or a category with Rfm Customer Segmentation: Amazon Buy Box Monitor (browser-act/skills, 6.1k stars), Tourmind Booking (tourmind-com/Tourmind-Booking-Skills, 1.8k stars), Ecommerce Image Suite (wzj177/ecommerce-image-suite, 449 stars) and Zach Feature Demand Validator (zach22-1999/amazon-skills, 209 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Rfm Customer Segmentation?
liangdabiao (a GitHub user) maintains it in liangdabiao/claude-data-analysis-ultra-main, which has 290 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on May 10, 2026.
Source: liangdabiao/claude-data-analysis-ultra-main on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.