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

• Consensus -> disagreement -> limitations -> gap synthesis discipline for survey prose

• 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, or typst-paper).

Note: survey-draft mode produces Markdown by default; for LaTeX output, it delegates final formatting to latex-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

Core Rules

• Ask the user the four intake questions (see references/question-flow.md) before starting any search or synthesis.

• Keep the skill workflow in English only, even when the requested report language is not English.

• Prefer recent arXiv plus top IEEE and automation venues over generic web articles.

• Default to the last 3 years, but keep seminal older work when it is still necessary for context.

• Cite every substantive claim and separate verified evidence from inference.

• In survey-draft mode, complete all structure and evidence phases before generating any prose. Structure phases produce YAML/tables only.

• Preserve contradictions explicitly; do not flatten conflicting findings into fake agreement.

Intake Contract

Always start by asking the four intake questions defined in references/question-flow.md:

• Report language (English / Simplified Chinese / Bilingual summary)

• Deliverable mode (research-brief / literature-map / venue-ranked survey / research-gap memo / survey-draft)

• Time window (last 12 months / last 3 years / last 5 years / custom)

• Industrial AI emphasis (predictive maintenance / intelligent scheduling / industrial anomaly detection / smart manufacturing and process optimization / CPS and edge AI / robotics crossover)

If the user does not choose, default to last 3 years and the subdomain implied by their prompt.

Intake Resolution Rules

• Resolve as many intake fields as possible from the user prompt before asking follow-up questions.

• If all four intake fields are already explicit or safely inferable, do not restate them as questions; lock them, announce the locked choices, and proceed.

• If some intake fields are missing, ask only for the missing fields in one compact follow-up block rather than re-asking the full questionnaire.

• If the user asks for the "latest", "recent", "current", or "today's" work without a window, default to last 12 months and report the absolute year span you used in the final scope note.

• If the topic is clearly outside Industrial AI scope, stop before search, name the boundary, and offer the closest supported framing instead of forcing a bad search.

• If the user explicitly says "stop after outline" or another survey checkpoint, honor that checkpoint and do not advance to the next survey phase automatically.

Required Inputs

• A concrete Industrial AI topic or question.

• User choices for report language, deliverable mode, time window, and domain emphasis.

• Optional preferences on peer-reviewed-only filtering, benchmarks vs deployment evidence, or desired output format.

If any intake item is missing, ask only for the unresolved items from references/question-flow.md before you search.

Source Strategy

Read these files before searching:

• references/source-priority.md

• references/venue-map.md

Primary sources:

• arXiv: eess.SY, cs.AI

• IEEE and automation anchors: T-ASE, CASE

Supporting crossover sources:

• arXiv: cs.RO, cs.LG

• IEEE robotics venues: ICRA, IROS, RA-L, T-RO

• Adjacent industrial and control venues listed in references/venue-map.md

When the user asks for the latest work, prefer:

• arXiv recent streams for rapid updates

• top IEEE and automation venues for stronger publication filtering

• secondary crossover venues only when they materially improve coverage

Workflow

Phase 1. Scope

• Rewrite the request as a precise Industrial AI research objective.

• Lock the report language, deliverable mode, time window, and domain emphasis.

• State explicit in-scope and out-of-scope boundaries.

Phase 2. Search Plan

• Build venue buckets and keyword groups from references/source-priority.md.

• Separate primary sources from secondary crossover sources.

• State the recency policy and any seminal-paper exceptions.

Phase 3. Source Collection

• Gather papers from the prioritized source buckets.

• Prefer official venue pages, arXiv recent listings, IEEE Xplore landing pages, and publisher or conference pages.

• Record why each paper was included.

Phase 4. Verification and Triage

• Check venue quality, publication type, year, and relevance.

• Remove weak matches, duplicates, and generic blog-style sources.

• Mark unreviewed preprints as preprints.

Phase 5. Synthesis

• Cluster the shortlisted papers by problem, method, dataset, deployment setting, and evaluation style.

• Surface trends, gaps, contradictions, and under-explored opportunities.

• When contradictions exist, state them before drawing any research-gap conclusion.

• Run a contrarian pass: what would challenge the dominant conclusion?

Phase 6. Report Assembly

Use the stable report structure from references/report-modes.md.

Every final report must include:

• search scope

• source buckets by venue

• shortlisted papers

• synthesis of trends and gaps

• recommended next reading or next experiments

Survey-Draft Workflow (Phases S1–S4)

When the user selects survey-draft, Phases 1–4 (Scope, Search Plan, Source Collection, Verification) execute as normal, then S1–S4 replace the original Phases 5–6.

#### Phase S1. Outline Building

Read references/modules/SURVEY_OUTLINE.md.

• Extract a taxonomy from the verified literature.

• Build the section skeleton as structured YAML.

• Present the outline to the user for approval.

• CHECKPOINT: do not enter S2 until the user approves the outline.

#### Phase S2. Evidence Pack Assembly

Read references/modules/SURVEY_EVIDENCE.md.

• Assemble an evidence pack for every H3 subsection.

• Lock the citation scope for each subsection.

• Produce structured evidence bundles (no prose).

#### Phase S3. Section-by-Section Writing

Read references/modules/SURVEY_WRITER.md.

• Draft each H3 independently, grounded in its evidence pack.

• Run the self-check gate on every H3 (depth, citation scope, tone).

• Produce one Markdown file per H2 section.

#### Phase S4. Merge and Quality Gate

Read references/modules/SURVEY_MERGE.md.

• Merge all section drafts into a single document.

• Run cross-section consistency checks.

• Apply the final quality checklist.

• If the user requested LaTeX output, delegate to latex-paper-en.

Deliverable Modes

Read references/report-modes.md and follow the selected mode exactly.

• research-brief: short, decision-ready overview

• literature-map: thematic map across methods and subproblems

• venue-ranked survey: grouped by source quality and venue tier

• research-gap memo: open problems, design space, and next-step opportunities

• survey-draft: taxonomy-driven survey manuscript with outline-first writing and optional LaTeX export

Output Contract

• State the locked intake choices and any defaults you applied before synthesis.

• Include a short search-method note: venue buckets used, recency policy, and any fallback or broadening step you had to apply.

• Distinguish verified evidence from inference in every deliverable.

• Label preprints explicitly as preprints.

• For non-survey modes, produce a structured report that includes: scope, source buckets, shortlisted papers, synthesis, and next reading or next experiments.

• For survey-draft, keep stage outputs format-specific:

• S1: YAML outline only

• S2: evidence packs or tables only

• S3: section Markdown drafts grounded in the evidence packs

• S4: merged Markdown survey with cross-section consistency notes

• Survey prose should prefer consensus -> disagreement -> limitations -> gap over paper-by-paper narration.

• If sources are sparse, inaccessible, or off-scope, say so directly and report the exact fallback you used.

Module Router

Module

Use when

Primary action

Read next

research

User selects any of the 4 report modes

Execute Phase 1–6 workflow

references/report-modes.md

survey-outline

User selects survey-draft (Phase S1)

Build taxonomy and section skeleton

references/modules/SURVEY_OUTLINE.md

survey-evidence

Outline approved by user (Phase S2)

Assemble per-H3 evidence packs

references/modules/SURVEY_EVIDENCE.md

survey-write

Evidence packs complete (Phase S3)

Draft prose per H3

references/modules/SURVEY_WRITER.md

survey-merge

All sections complete (Phase S4)

Merge, quality gate, optional LaTeX handoff

references/modules/SURVEY_MERGE.md

This skill is LLM-driven and does not include executable scripts. All phases are executed through web search, structured synthesis, and prompting.

Quality Bar

Read references/quality-checklist.md before finalizing.

Non-negotiable standards:

• no unsupported claims

• no venue-blind source mixing

• no hiding contradictions

• no synthesized report before intake questions are answered

• no generic "latest research says" language without source-backed evidence

Error Handling

• Zero results: Broaden keywords, relax the time window by one tier, and try adjacent venues. If still empty, report the negative result with the exact queries attempted.

• Off-subdomain topic: State that the topic falls outside Industrial AI scope, suggest the closest supported subdomain, and ask the user whether to proceed or abort.

• Inaccessible databases: Note which sources were unreachable, proceed with available sources, and flag the gap in the final report.

• Too few papers (<5 shortlisted): Lower the time window threshold, include Tier 2/3 venues, and explicitly note the thin evidence base in the synthesis.

Reference Map

File

Phase

When to read

references/question-flow.md

Intake

Before asking the user any questions

references/source-priority.md

Search Plan

Before building venue buckets

references/venue-map.md

Search Plan

Before selecting specific venues

references/report-modes.md

Report Assembly

Before structuring the final output

references/quality-checklist.md

Report Assembly

Before finalizing the report

references/modules/SURVEY_OUTLINE.md

Survey S1

When building the survey outline

references/modules/SURVEY_EVIDENCE.md

Survey S2

When assembling evidence packs

references/modules/SURVEY_WRITER.md

Survey S3

When drafting survey sections

references/modules/SURVEY_MERGE.md

Survey S4

When merging and running quality gate

references/SURVEY_WRITING_GUIDE.md

Survey S1–S4

Survey writing philosophy reference

Examples

• examples/predictive-maintenance.md

• examples/intelligent-scheduling.md

• examples/industrial-anomaly-detection.md

• examples/survey-predictive-maintenance.md

Example Requests

• “Research recent predictive maintenance papers from the last 3 years and return a research-brief.”

• “Compare industrial anomaly detection papers across arXiv and IEEE automation venues, and show contradictions in evaluation setups.”

• “Draft a survey on intelligent scheduling for researchers new to the subfield, but stop after the YAML outline for approval.”

• “My topic is warehouse picking robotics. If that is outside scope, tell me the closest supported Industrial AI framing and proceed only with that.”

Boundaries

This v1 skill does not implement:

• systematic review mode

• meta-analysis

• IRB-heavy or clinical ethics branches

• standalone automation scripts

If the user needs those, state the boundary and continue with the closest supported research mode.