Longbridge Quant
helsome/folio
Quantitative strategy frameworks: pairs trading/cointegration, volatility regime strategies, seasonality/calendar effects, multi-factor models (IC/IR), factor research and screening, correlation…
Agent skill
Big Data Labeling Variable Construction
Route text-labeling requests across LDA topic modeling, sklearn baselines, pretrained transformer models, and OpenAI-compatible LLM labeling.
Install Big Data Labeling Variable Construction
$ npx skills add Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit big-data-labeling-variable-construction --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/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction' .claude/skills/big-data-labeling-variable-construction && 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 "big-data-labeling-variable-construction" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-construction into .claude/skills/big-data-labeling-variable-construction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "big-data-labeling-variable-construction", 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/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-constructionType 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 Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit big-data-labeling-variable-construction --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction' .agents/skills/big-data-labeling-variable-construction && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "big-data-labeling-variable-construction" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-construction into .agents/skills/big-data-labeling-variable-construction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "big-data-labeling-variable-construction", 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 Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit big-data-labeling-variable-construction --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction' .cursor/skills/big-data-labeling-variable-construction && 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 "big-data-labeling-variable-construction" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-construction into .cursor/skills/big-data-labeling-variable-construction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "big-data-labeling-variable-construction", 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/Drchronx/ai-agent-research-starter-kit.git --path '综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction'--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 Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit big-data-labeling-variable-construction --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction' .gemini/skills/big-data-labeling-variable-construction && 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 "big-data-labeling-variable-construction" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-construction into .gemini/skills/big-data-labeling-variable-construction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "big-data-labeling-variable-construction", 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 Drchronx/ai-agent-research-starter-kit big-data-labeling-variable-constructionInstalls 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 Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/'综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction' .github/skills/big-data-labeling-variable-construction && 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 "big-data-labeling-variable-construction" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-construction into .github/skills/big-data-labeling-variable-construction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "big-data-labeling-variable-construction", 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 Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit big-data-labeling-variable-construction --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction' .opencode/skills/big-data-labeling-variable-construction && 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 "big-data-labeling-variable-construction" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/05_%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98%E4%B8%8ENLP%20Skills/big-data-labeling-variable-construction into .opencode/skills/big-data-labeling-variable-construction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "big-data-labeling-variable-construction", 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
big-data-labeling-variable-construction- GitHub stars
- 134
- Token cost
- ~1.1k tokens
- SKILL.md length
- 318 words
- Files
- 23 (incl. scripts, assets)
- Skills in repo
- 53
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Route text-labeling requests across LDA topic modeling, sklearn baselines, pretrained transformer models, and OpenAI-compatible LLM labeling.
- Works in 8 steps: Recommend a route → Prepare a confirmation plan from the… → Wait for user confirmation → …
- Tasks that involve Data cleaning
- SKILL.md covers Mandatory interaction pattern, What the user usually does not…, What the user still needs to… and Recommended flow, plus 3 more sections
- Runs Python scripts from its folder; calls python; reaches api.openai.com
What it does
Big Data Labeling Variable Construction is an agent skill from Drchronx/ai-agent-research-starter-kit. Route text-labeling requests across LDA topic modeling, sklearn baselines, pretrained transformer models, and OpenAI-compatible LLM labeling. First inspect the dataset and infer columns/defaults automatically, then wait for explicit user confirmation before execution.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 25 other files, including scripts and assets (for example `agents/openai.yaml`, `scripts/bert_labeling.py` and `scripts/build_empirical_variables.py`).
It sits in Data & Analytics, covering Data cleaning, Machine learning and Natural language processing. It works with scikit-learn, OpenAI and PyTorch. The repository describes itself as: AI Agent 科研全流程教学包，能教学生从零部署 Codex、Claude Code、OpenClaw、Hermes 等 Agent，学会使用 Skills、飞书、AMiner、AI4Scholar、Zotero、Obsidian…
When your agent uses it
- Tasks that involve Data cleaning
- Tasks that involve Machine learning
- Tasks that involve Natural language processing
Example prompts
- “/big-data-labeling-variable-construction”
Requirements
- Python 3
- A credential in YOUR_KEY
Workflow steps
8 steps, taken from the step headings in SKILL.md.
- Recommend a route
- Prepare a confirmation plan from the dataset
- Wait for user confirmation
- Run the actual method script
- LDA主题建模
- sklearn常见机器学习方法
- 预训练模型
- 调用大语言模型标注数据
What it can do on your machine
Read from SKILL.md and the folder at commit aab1133. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 13 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api.openai.com
Also links to:
pytorch.org
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
Big Data Labeling Variable Construction loads about 1.1k tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 318 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 passed
The automated check found no risky patterns in SKILL.md.
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); the scripts in this folder are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 318 words (~1,147 tokens).
- name
- big-data-labeling-variable-construction
Files
SKILL.md and 22 other files (scripts, assets) in 综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction of Drchronx/ai-agent-research-starter-kit.
- SKILL.md
- agents/openai.yaml
- assets/sample_labeled_text_dataset.csv
- assets/sample_text_dataset.csv
- assets/sample_topic_corpus.csv
- scripts/bert_labeling.py
- scripts/build_empirical_variables.py
- scripts/check_pretrained_env.py
- scripts/diagnose_torch_runtime.py
- scripts/ernie_labeling.py
- scripts/labeling_common.py
- scripts/labeling_workflow.py
- scripts/lda_topic_model.py
- scripts/openai_llm_labeling.py
- scripts/prepare_labeling_plan.py
- scripts/requirements.txt
- scripts/sklearn_knn_labeling.py
- scripts/sklearn_labeling_common.py
- … and 5 more
Open the folder on GitHubat commit aab1133
Compare with similar skills
Big Data Labeling Variable Construction 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 |
|---|---|---|---|---|---|---|
| Big Data Labeling Variable Construction this skillDrchronx/ai-agent-research-starter-kit | 134 | — | ~1.1k | Automated safety check: Pass | Custom licence | |
| Longbridge Quanthelsome/folio | 269 | 1 repos | ~1.6k | Automated safety check: Pass | MIT | |
| ML EngineerRightNow-AI/openfang | 18k | — | ~987 | Automated safety check: Pass | Apache-2.0 | |
| ML Model Trainingsecondsky/claude-skills | 227 | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Scikit Learn Machine Learningjaechang-hits/SciAgent-Skills | 370 | 1 repos | ~4k | Automated safety check: Pass | BSD-3-Clause | |
| Deep Learningericrisco/rsc-harness | 156 | — | ~3.4k | Automated safety check: Pass | MIT |
Similar skills
ML Engineer
RightNow-AI/openfang
Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps
ML Model Training
secondsky/claude-skills
Train ML models with scikit-learn, PyTorch, TensorFlow. An agent skill from secondsky/claude-skills.
Scikit Learn Machine Learning
jaechang-hits/SciAgent-Skills
Classical ML in Python: classification, regression, clustering, dim reduction, evaluation, tuning, preprocessing pipelines.
Deep Learning
ericrisco/rsc-harness
A skill your agent uses when training or debugging a neural net in PyTorch — the forward/loss/backward/step loop and its silent bugs, mixed precision (AMP), AdamW/LR schedules, DDP/FSDP/ZeRO…
Machine Learning
ericrisco/rsc-harness
A skill your agent uses when predicting a column from rows of tabular features with classic models — scikit-learn pipelines, RandomForest, XGBoost/LightGBM, leak-free cross-validation, metrics for…
More from Drchronx/ai-agent-research-starter-kit
All 53 skills in this repoLiterature Reviewer Skill
Drchronx/ai-agent-research-starter-kit
Build high-quality literature reviews from a research topic using a 10-phase workflow.
Scenario Experiment Analysis
Drchronx/ai-agent-research-starter-kit
Analyze scenario/vignette experiment datasets for behavioral research.
Scenario Experiment Benchmark Mining
Drchronx/ai-agent-research-starter-kit
Mine and synthesize real top-journal scenario/vignette experiment patterns for behavioral research.
Web Browsing
Drchronx/ai-agent-research-starter-kit
Browse and summarize websites, extract content from URLs, search the web for information.
Multi Source Data Integration Extraction
Drchronx/ai-agent-research-starter-kit
Automatically merge scattered Excel and CSV files, normalize column names, and extract structured tables from PDF, HTML, TXT, or Markdown documents.
Scientific Slides
Drchronx/ai-agent-research-starter-kit
Build slide decks and presentations for research talks using Nano Banana Pro AI.
Related
Works with
Categories
Questions about Big Data Labeling Variable Construction
What does Big Data Labeling Variable Construction do?
Route text-labeling requests across LDA topic modeling, sklearn baselines, pretrained transformer models, and OpenAI-compatible LLM labeling. Big Data Labeling Variable Construction is an agent skill from Drchronx/ai-agent-research-starter-kit. Route text-labeling requests across LDA topic modeling, sklearn baselines, pretrained transformer models, and OpenAI-compatible LLM labeling.
When should I use Big Data Labeling Variable Construction?
Big Data Labeling Variable Construction fits situations like: tasks that involve Data cleaning; tasks that involve Machine learning; tasks that involve Natural language processing.
How do I install Big Data Labeling Variable Construction in Claude Code?
Run `npx skills add Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a claude-code`. Or copy the skill folder (综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction in Drchronx/ai-agent-research-starter-kit) into .claude/skills/big-data-labeling-variable-construction in your project. Claude Code loads it when a task matches its description.
How do I install Big Data Labeling Variable Construction in Codex?
Run `npx skills add Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a codex`. Or copy the skill folder (综合学术部署包/05_文本挖掘与NLP Skills/big-data-labeling-variable-construction in Drchronx/ai-agent-research-starter-kit) into .agents/skills/big-data-labeling-variable-construction in your project. Codex loads it when a task matches its description.
Can I use Big Data Labeling Variable Construction 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 Drchronx/ai-agent-research-starter-kit --skill big-data-labeling-variable-construction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/big-data-labeling-variable-construction, .gemini/skills/big-data-labeling-variable-construction, .github/skills/big-data-labeling-variable-construction and .opencode/skills/big-data-labeling-variable-construction in your project.
What does Big Data Labeling Variable Construction need to run?
Going by SKILL.md and its folder, Big Data Labeling Variable Construction needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; A credential in YOUR_KEY.
Does Big Data Labeling Variable Construction access the network?
SKILL.md names 2 domains. In commands or code: api.openai.com; the agent is likely to contact it when it follows the instructions. As links in the text: pytorch.org. This is read from the text; nothing was executed.
Is Big Data Labeling Variable Construction safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Big Data Labeling Variable Construction use?
Big Data Labeling Variable Construction has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Big Data Labeling Variable Construction use?
About 1.1k tokens (SKILL.md is roughly 4.6k 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 Big Data Labeling Variable Construction?
Skills that share tags, products or a category with Big Data Labeling Variable Construction: Longbridge Quant (helsome/folio, 269 stars), ML Engineer (RightNow-AI/openfang, 18k stars), ML Model Training (secondsky/claude-skills, 227 stars) and Scikit Learn Machine Learning (jaechang-hits/SciAgent-Skills, 370 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Big Data Labeling Variable Construction?
Drchronx (a GitHub user) maintains it in Drchronx/ai-agent-research-starter-kit, which has 134 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on May 19, 2026.
Source: Drchronx/ai-agent-research-starter-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.