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.
npx skills add arnabdeypolimi/claude_code_setup --skill industrial-ai-researchgit clone --depth 1 https://github.com/arnabdeypolimi/claude_code_setupWrote 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.
[](https://agentmods.dev/skills/arnabdeypolimi/claude_code_setup/industrial-ai-research)<a href="https://agentmods.dev/skills/arnabdeypolimi/claude_code_setup/industrial-ai-research"><img src="https://agentmods.dev/badge/skills/arnabdeypolimi/claude_code_setup/industrial-ai-research/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.
<a href="https://agentmods.dev/skills/arnabdeypolimi/claude_code_setup/industrial-ai-research"><img src="https://agentmods.dev/badge/skills/arnabdeypolimi/claude_code_setup/industrial-ai-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.02827 |
| Opus 5 | $0.00000 | $0.01413 |
| Sonnet 5 | $0.00000 | $0.00565 |
| Haiku 4.5 | $0.00000 | $0.00283 |
Grade A, and why
industrial-ai-research 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Industrial AI Research
Run a lean, source-aware research workflow for Industrial AI.
Capability Summary
- Structured literature research for Industrial AI and automation topics
- Mandatory four-question intake before any search or synthesis
- Venue-aware source prioritization (arXiv, IEEE, automation venues)
- Four deliverable modes: research-brief, literature-map, venue-ranked survey, research-gap memo
- Contrarian synthesis pass to surface contradictions and under-explored gaps
- Survey draft generation: outline-first writing with per-section evidence packs and optional LaTeX export
Triggering
Use this skill when the user wants to:
- Survey Industrial AI literature on a specific subtopic
- Compare papers across venues or methods within Industrial AI
- Identify research gaps in predictive maintenance, scheduling, anomaly detection, or smart manufacturing
- Produce a structured research report with source-backed evidence
- Draft a structured survey on an Industrial AI subtopic
- Produce a survey manuscript with taxonomy, evidence packs, and section-by-section writing
Do Not Use
- Writing or compiling LaTeX/Typst papers (use
latex-paper-en,latex-thesis-zh, ortypst-paper). Note: survey-draft mode produces Markdown by default; for LaTeX output, it delegates final formatting tolatex-paper-en. - Auditing paper quality or formatting (use
paper-audit) - Systematic reviews or meta-analyses requiring IRB or clinical ethics
- Topics outside the Industrial AI and automation domain
- Auditing an existing paper's quality or formatting (use
paper-audit) - Editing LaTeX/Typst source files (use the appropriate writing skill)
Safety Boundaries
- Never fabricate paper metadata (title, authors, venue, year, DOI)
- Never present preprints as peer-reviewed publications
- Never start synthesis before intake questions are answered
- Never suppress contradictions or conflicting evidence
- Never use Tier 4 sources (blogs, press releases) as primary evidence
What ships with it
16 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.
- agents/openai.yaml 420 B
- evals/evals.json 6.5 KB
- examples/industrial-anomaly-detection.md 562 B
- examples/intelligent-scheduling.md 521 B
- examples/predictive-maintenance.md 536 B
- examples/survey-predictive-maintenance.md 8.8 KB
- references/modules/SURVEY_EVIDENCE.md 3.8 KB
- references/modules/SURVEY_MERGE.md 4.4 KB
- references/modules/SURVEY_OUTLINE.md 4.0 KB
- references/modules/SURVEY_WRITER.md 4.3 KB
- references/quality-checklist.md 1.2 KB
- references/question-flow.md 1.8 KB
- references/report-modes.md 2.9 KB
- references/source-priority.md 2.2 KB
- references/SURVEY_WRITING_GUIDE.md 6.3 KB
- references/venue-map.md 2.9 KB
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.
- 8d ago First seen · 271 lines · 0 tokens per session scan A 60f135f8999f
industrial-ai-research is a skill published in the GitHub repository arnabdeypolimi/claude_code_setup (4 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,827 tokens. 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 2026-08-31.
Other skills, from other repositories
bitcoin-secp256k1
The elliptic curve Bitcoin uses for all signatures (ECDSA + Schnorr). Defined by SECG (SEC 2: Recommended Elliptic Curve Domain Parameters).
scientific-method
Use this skill whenever someone doubts a number, demands rigorous proof of a cause, or wants something invented and proven — any time a benchmark, metric, ceiling, or root-cause story must be verified rather than trusted, or a limit must be broken with a built, measured mechanism. Typical situations: a measurement…
daily-paper-generator
Use when the user asks to generate daily paper digests on a general topic. This skill supports both arXiv and bioRxiv (or either one), then produces structured Chinese/English summaries for selected papers.
huggingface-llm-trainer
Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion. Use for cloud LLM training; use huggingface-vision-trainer for vision tasks.
feature-dev
Guide a feature implementation through a structured seven-phase workflow with deep codebase understanding, clarifying questions, parallel architecture design, and quality review. Use this skill when the user asks to build a new feature, add functionality, or wants a methodical approach to implementation rather than…
memstack-business-gdpr
Use this skill when the user says 'GDPR', 'data protection', 'privacy compliance', 'DPA', 'DSAR', 'data subject request', 'cookie consent', 'privacy audit', 'CCPA', or asks 'do I need GDPR for this repo'. Scans the repository to detect what personal data is collected, classifies sensitivity, determines whether GDPR…