Matplotlib
zLanqing/codex-claude-academic-skills
Low-level plotting library for full customization. An agent skill from zLanqing/codex-claude-academic-skills.
基于RFM模型和回归算法的客户生命周期价值(LTV)预测分析工具，支持电商和零售业务的客户价值预测。使用时需要客户交易数据、订单历史或消费记录，自动进行RFM特征工程、回归建模和价值预测。
Install Ltv Predictor
$ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill ltv-predictor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main ltv-predictor --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/ltv-predictor .claude/skills/ltv-predictor && 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 "ltv-predictor" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/ltv-predictor into .claude/skills/ltv-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ltv-predictor", 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/ltv-predictorType 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 ltv-predictor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main ltv-predictor --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/ltv-predictor .agents/skills/ltv-predictor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ltv-predictor" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/ltv-predictor into .agents/skills/ltv-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ltv-predictor", 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 ltv-predictor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main ltv-predictor --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/ltv-predictor .cursor/skills/ltv-predictor && 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 "ltv-predictor" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/ltv-predictor into .cursor/skills/ltv-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ltv-predictor", 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/ltv-predictor--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 ltv-predictor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install liangdabiao/claude-data-analysis-ultra-main ltv-predictor --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/ltv-predictor .gemini/skills/ltv-predictor && 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 "ltv-predictor" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/ltv-predictor into .gemini/skills/ltv-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ltv-predictor", 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 ltv-predictorInstalls 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 ltv-predictor -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/ltv-predictor .github/skills/ltv-predictor && 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 "ltv-predictor" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/ltv-predictor into .github/skills/ltv-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ltv-predictor", 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 ltv-predictor -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 ltv-predictor --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/ltv-predictor .opencode/skills/ltv-predictor && 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 "ltv-predictor" agent skill from https://github.com/liangdabiao/claude-data-analysis-ultra-main/tree/main/.claude/skills/ltv-predictor into .opencode/skills/ltv-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ltv-predictor", 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
ltv-predictor- GitHub stars
- 290
- Token cost
- ~1.4k tokens
- SKILL.md length
- 205 words
- Files
- 30
- Skills in repo
- 19
- Repo updated
- First seen
- Licence
- None found
At a glance
基于RFM模型和回归算法的客户生命周期价值(LTV)预测分析工具，支持电商和零售业务的客户价值预测。使用时需要客户交易数据、订单历史或消费记录，自动进行RFM特征工程、回归建模和价值预测。
- Works in 3 steps: 环境安装 → 基础使用 → 快速示例
- Data & Analytics work in your project
- SKILL.md covers ✨ 核心功能, 🚀 快速开始, 📁 技能结构 and 🎯 应用场景, plus 5 more sections
- Runs Python scripts from its folder; calls pip
What it does
Ltv Predictor is an agent skill from liangdabiao/claude-data-analysis-ultra-main. 基于RFM模型和回归算法的客户生命周期价值(LTV)预测分析工具，支持电商和零售业务的客户价值预测。使用时需要客户交易数据、订单历史或消费记录，自动进行RFM特征工程、回归建模和价值预测。
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 32 other files (for example `CHANGELOG.md`, `PROJECT_SUMMARY.md` and `README.md`).
It sits in Data & Analytics. 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
- Data & Analytics work in your project
Example prompts
- “/ltv-predictor”
Requirements
- Python 3
- Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, WebSearch
Workflow steps
3 steps, taken from the step headings in SKILL.md.
- 环境安装
- 基础使用
- 快速示例
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:
ReadWriteEditBashGlobGrepWebSearch
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
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
Ltv Predictor loads about 1.4k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 205 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, Edit, Bash, Glob, Grep, WebSearch
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 205 words (~1,372 tokens).
- name
- ltv-predictor
- allowed-tools
- Read, Write, Edit, Bash, Glob, Grep, WebSearch
Files
SKILL.md and 29 other files in .claude/skills/ltv-predictor of liangdabiao/claude-data-analysis-ultra-main.
- SKILL.md
- CHANGELOG.md
- PROJECT_SUMMARY.md
- README.md
- docs/QUICK_START.md
- examples/advanced_analytics.py
- examples/data_processor.py
- examples/deployment_manager.py
- examples/ecommerce_ltv_analysis.py
- examples/ltv_predictor.py
- examples/model_optimizer.py
- examples/quick_analysis.py
- examples/quick_ltv_prediction.py
- examples/quick_prediction/new_customer_predictions.csv
- examples/quick_prediction/new_customers.csv
- examples/regression_models.py
- examples/report_generator.py
- examples/sample_data
- … and 12 more
Open the folder on GitHubat commit 6b52856
Compare with similar skills
Ltv Predictor 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 |
|---|---|---|---|---|---|---|
| Ltv Predictor this skillliangdabiao/claude-data-analysis-ultra-main | 290 | — | ~1.4k | Automated safety check: Notes | None | |
| MatplotlibzLanqing/codex-claude-academic-skills | 4.7k | 17 repos | ~2.9k | Automated safety check: Pass | MIT | |
| Exploratory Data Analysisspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Scikit LearnzLanqing/codex-claude-academic-skills | 4.7k | 16 repos | ~3.9k | Automated safety check: Pass | BSD-3-Clause | |
| Chart Visualizationbytedance/deer-flow | 84k | 2 repos | ~840 | Automated safety check: Pass | MIT | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Exploratory Data Analysis
spacering-net/codeg
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
Scikit Learn
zLanqing/codex-claude-academic-skills
Machine learning in Python with scikit-learn. An agent skill from zLanqing/codex-claude-academic-skills.
Chart Visualization
bytedance/deer-flow
Picks a suitable chart type from 26 options for your data, maps the data to that chart's parameters and generates a chart image through a JavaScript script.
TimesFM Forecasting
google-research/timesfm
Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.
- Official
Sandbox Bench
vercel/next.js
Benchmark React or Next.js changes on Vercel Sandbox VMs with paired A/B statistics: react PR/commit vs base, or Next.js PR/commit vs base, measured end-to-end through the bench/render-pipeline app…
More from liangdabiao/claude-data-analysis-ultra-main
All 19 skills in this repoFunnel Analysis
liangdabiao/claude-data-analysis-ultra-main
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities.
Retention Analysis
liangdabiao/claude-data-analysis-ultra-main
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning.
Attribution Analysis Modeling
liangdabiao/claude-data-analysis-ultra-main
Perform multi-touch attribution analysis using Markov chains, Shapley values, and custom attribution models.
Code Generator
liangdabiao/claude-data-analysis-ultra-main
Generates production-ready analysis code in Python, R, SQL. An agent skill from liangdabiao/claude-data-analysis-ultra-main.
Content Analysis
liangdabiao/claude-data-analysis-ultra-main
Analyze text content using both traditional NLP and LLM-enhanced methods.
Data Explorer
liangdabiao/claude-data-analysis-ultra-main
Performs exploratory data analysis, statistical analysis, and pattern discovery.
Related
Categories
Questions about Ltv Predictor
What does Ltv Predictor do?
基于RFM模型和回归算法的客户生命周期价值(LTV)预测分析工具，支持电商和零售业务的客户价值预测。使用时需要客户交易数据、订单历史或消费记录，自动进行RFM特征工程、回归建模和价值预测。. Ltv Predictor is an agent skill from liangdabiao/claude-data-analysis-ultra-main.
When should I use Ltv Predictor?
Ltv Predictor fits situations like: data & Analytics work in your project.
How do I install Ltv Predictor in Claude Code?
Run `npx skills add liangdabiao/claude-data-analysis-ultra-main --skill ltv-predictor -a claude-code`. Or copy the skill folder (.claude/skills/ltv-predictor in liangdabiao/claude-data-analysis-ultra-main) into .claude/skills/ltv-predictor in your project. Claude Code loads it when a task matches its description.
How do I install Ltv Predictor in Codex?
Run `npx skills add liangdabiao/claude-data-analysis-ultra-main --skill ltv-predictor -a codex`. Or copy the skill folder (.claude/skills/ltv-predictor in liangdabiao/claude-data-analysis-ultra-main) into .agents/skills/ltv-predictor in your project. Codex loads it when a task matches its description.
Can I use Ltv Predictor 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 ltv-predictor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ltv-predictor, .gemini/skills/ltv-predictor, .github/skills/ltv-predictor and .opencode/skills/ltv-predictor in your project.
What does Ltv Predictor need to run?
Going by SKILL.md and its folder, Ltv Predictor needs Python for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, WebSearch.
Does Ltv Predictor access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Ltv Predictor 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 Ltv Predictor use?
No licence was found for Ltv Predictor or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Ltv Predictor use?
About 1.4k tokens (SKILL.md is roughly 5.5k 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 Ltv Predictor?
Skills that share tags, products or a category with Ltv Predictor: Matplotlib (zLanqing/codex-claude-academic-skills, 4.7k stars), Exploratory Data Analysis (spacering-net/codeg, 3.9k stars), Scikit Learn (zLanqing/codex-claude-academic-skills, 4.7k stars) and Chart Visualization (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ltv Predictor?
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.