Threat Detection
alirezarezvani/claude-skills
A skill your agent uses when hunting for threats in an environment, analyzing IOCs, or detecting behavioral anomalies in telemetry.
Agent skill
Industrial AI Research
by brycewang-stanford in brycewang-stanford/Auto-Empirical-Research-Skills
Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation.
Install Industrial AI Research
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills industrial-ai-research --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/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research .claude/skills/industrial-ai-research && 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 "industrial-ai-research" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research into .claude/skills/industrial-ai-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "industrial-ai-research", 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/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-researchType 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills industrial-ai-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research .agents/skills/industrial-ai-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "industrial-ai-research" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research into .agents/skills/industrial-ai-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "industrial-ai-research", 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills industrial-ai-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research .cursor/skills/industrial-ai-research && 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 "industrial-ai-research" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research into .cursor/skills/industrial-ai-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "industrial-ai-research", 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/brycewang-stanford/Auto-Empirical-Research-Skills.git --path skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research--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 brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills industrial-ai-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research .gemini/skills/industrial-ai-research && 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 "industrial-ai-research" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research into .gemini/skills/industrial-ai-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "industrial-ai-research", 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 brycewang-stanford/Auto-Empirical-Research-Skills industrial-ai-researchInstalls 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research .github/skills/industrial-ai-research && 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 "industrial-ai-research" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research into .github/skills/industrial-ai-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "industrial-ai-research", 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills industrial-ai-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research .opencode/skills/industrial-ai-research && 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 "industrial-ai-research" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research into .opencode/skills/industrial-ai-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "industrial-ai-research", 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
industrial-ai-research- GitHub stars
- 4.6k
- Token cost
- ~3.3k tokens
- SKILL.md length
- 1,452 words
- Files
- 17 (incl. references)
- Skills in repo
- 383
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation.
- Works in 6 steps: Scope → Search Plan → Source Collection → …
- The user needs up-to-date research on predictive maintenance
- SKILL.md covers Capability Summary, Triggering, Do Not Use and Safety Boundaries, plus 14 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Industrial AI Research is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation. Use when the user needs up-to-date research on predictive maintenance, intelligent scheduling, industrial anomaly detection, smart manufacturing, cyber-physical systems, edge AI for automation, or crossover robotics-for-industry topics. Also trigger for adjacent terms: "digital twin", "industrial IoT", "Industry 4.0", "manufacturing AI", "factory…
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 21 other files, including reference files (for example `agents/openai.yaml`, `evals/evals.json` and `examples/industrial-anomaly-detection.md`).
It sits in Data & Analytics, covering Anomaly detection and Prioritization frameworks. It works with LaTeX. The repository describes itself as: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI…
When your agent uses it
- The user needs up-to-date research on predictive maintenance
- Intelligent scheduling
- Industrial anomaly detection
- Smart manufacturing
Example prompts
- “digital twin”
- “industrial IoT”
- “Industry 4.0”
- “/industrial-ai-research”
Requirements
- Pre-approved tools (allowed-tools): Read, Glob, Grep, WebSearch, WebFetch
Workflow steps
6 steps, taken from the step headings in SKILL.md.
- Scope
- Search Plan
- Source Collection
- Verification and Triage
- Synthesis
- Report Assembly
What it can do on your machine
Read from SKILL.md and the folder at commit 9fa87d8. 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:
ReadGlobGrepWebSearchWebFetch
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
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
Industrial AI Research loads about 3.3k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 152 tokens; SKILL.md has 1,452 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); files beside SKILL.md 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 1,452 words (~3,251 tokens).
“Run a lean, source-aware research workflow for Industrial AI.”
- name
- industrial-ai-research
- allowed-tools
- Read, Glob, Grep, WebSearch, WebFetch
- metadata.category
- academic-writing
- metadata.tags
- industrial-ai, research, literature-review, predictive-maintenance, scheduling, anomaly-detection, smart-manufacturing, cps, arxiv, ieee, survey, survey-draft
- metadata.version
- 1.1
- metadata.last_updated
- 2026-03-12
- argument-hint
- [topic] [--mode MODE] [--lang LANG] [--window WINDOW] [--output-dir DIR]
Files
SKILL.md and 16 other files (references) in skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research of brycewang-stanford/Auto-Empirical-Research-Skills.
- SKILL.md
- agents/openai.yaml
- evals/evals.json
- examples/industrial-anomaly-detection.md
- examples/intelligent-scheduling.md
- examples/predictive-maintenance.md
- examples/survey-predictive-maintenance.md
- references/SURVEY_WRITING_GUIDE.md
- references/modules/SURVEY_EVIDENCE.md
- references/modules/SURVEY_MERGE.md
- references/modules/SURVEY_OUTLINE.md
- references/modules/SURVEY_WRITER.md
- references/quality-checklist.md
- references/question-flow.md
- references/report-modes.md
- references/source-priority.md
- … and 1 more
Open the folder on GitHubat commit 9fa87d8
Compare with similar skills
Industrial AI Research 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 |
|---|---|---|---|---|---|---|
| Industrial AI Research this skillbrycewang-stanford/Auto-Empirical-Research-Skills | 4.6k | — | ~3.3k | Automated safety check: Pass | Custom licence | |
| Threat Detectionalirezarezvani/claude-skills | 28k | — | ~3.5k | Automated safety check: Pass | MIT | |
| Comorbidity Common Immune Biomarker Research Planneraipoch/medical-research-skills | 1.9k | — | ~4.5k | Automated safety check: Pass | MIT | |
| Scientific Figure Generationlingzhi227/agent-research-skills | 390 | — | ~809 | Automated safety check: Pass | None | |
| Scholar Lingjoshzyj/open-scholar-skill | 168 | — | ~6.7k | Automated safety check: Pass | Custom licence | |
| Math Reasoninglingzhi227/agent-research-skills | 390 | — | ~639 | Automated safety check: Pass | None |
Similar skills
Comorbidity Common Immune Biomarker Research Planner
aipoch/medical-research-skills
Generates complete comorbidity-oriented shared-biomarker bioinformatics research designs from a user-provided disease pair and validation direction.
Scientific Figure Generation
lingzhi227/agent-research-skills
Generates publication-quality scientific figures with matplotlib or seaborn through query expansion, a run-and-retry coding loop and a visual check of the rendered PNG.
Scholar Ling
joshzyj/open-scholar-skill
Design and analyze studies in sociolinguistics, language variation, acoustic phonetics, discourse analysis, language contact, and computational linguistics.
Math Reasoning
lingzhi227/agent-research-skills
Formal mathematical reasoning for research papers — derive equations, write proofs, formalize problem settings, select statistical tests, and generate LaTeX math notation.
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.
More from brycewang-stanford/Auto-Empirical-Research-Skills
All 383 skills in this repoAer Consistency
brycewang-stanford/Auto-Empirical-Research-Skills
A skill your agent uses when auditing a finished or near-finished AER, AER:Insights, or AEJ manuscript for internal consistency: headline numbers across abstract, introduction, results, and tables…
Latex Paper En
brycewang-stanford/Auto-Empirical-Research-Skills
English LaTeX academic paper assistant for existing .tex projects.
Bayesian Workflow
brycewang-stanford/Auto-Empirical-Research-Skills
Opinionated Bayesian modeling workflow with PyMC and ArviZ. An agent skill from brycewang-stanford/Auto-Empirical-Research-Skills.
Daily Paper Generator
brycewang-stanford/Auto-Empirical-Research-Skills
A skill your agent uses when the user asks to "generate daily paper", "search arXiv for EEG papers", "find EEG decoding papers", "review brain-computer interface papers", or wants to create paper…
Five Questions
brycewang-stanford/Auto-Empirical-Research-Skills
Deeply analyze any empirical economics PDF using the five-question framework (五问框架): research question, identification strategy, core estimand, robustness logic, and scholarly contribution.
Kaggle Research
brycewang-stanford/Auto-Empirical-Research-Skills
A skill your agent uses when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an…
Related
Works with
Questions about Industrial AI Research
What does Industrial AI Research do?
Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation. Industrial AI Research is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Industrial AI literature research with mandatory intake questions, venue-aware source prioritization, structured report outputs, and survey draft generation.
When should I use Industrial AI Research?
Industrial AI Research fits situations like: the user needs up-to-date research on predictive maintenance; intelligent scheduling; industrial anomaly detection; smart manufacturing.
How do I install Industrial AI Research in Claude Code?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a claude-code`. Or copy the skill folder (skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/industrial-ai-research in your project. Claude Code loads it when a task matches its description.
How do I install Industrial AI Research in Codex?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a codex`. Or copy the skill folder (skills/35-bahayonghang-academic-writing-skills/skills/industrial-ai-research in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/industrial-ai-research in your project. Codex loads it when a task matches its description.
Can I use Industrial AI Research 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill industrial-ai-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/industrial-ai-research, .gemini/skills/industrial-ai-research, .github/skills/industrial-ai-research and .opencode/skills/industrial-ai-research in your project.
What does Industrial AI Research need to run?
SKILL.md names no scripts, command-line tools or credentials: Industrial AI Research is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Glob, Grep, WebSearch, WebFetch.
Does Industrial AI Research 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 Industrial AI Research 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. Review the folder before installing.
What licence does Industrial AI Research use?
Industrial AI Research 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 Industrial AI Research use?
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.6k tokens, read only when the agent opens those files.
What are the alternatives to Industrial AI Research?
Skills that share tags, products or a category with Industrial AI Research: Threat Detection (alirezarezvani/claude-skills, 28k stars), Comorbidity Common Immune Biomarker Research Planner (aipoch/medical-research-skills, 1.9k stars), Scientific Figure Generation (lingzhi227/agent-research-skills, 390 stars) and Scholar Ling (joshzyj/open-scholar-skill, 168 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Industrial AI Research?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,556 GitHub stars. The repository holds 383 skills in this directory. The repository was last updated on October 5, 2026.
Source: brycewang-stanford/Auto-Empirical-Research-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.