ARC Creator
/install arc-creator
ARC Creator
Create FAIR Digital Objects following the nfdi4plants ARC specification v3.0.0.
Prerequisites
gitandgit-lfsinstalled- ARC Commander CLI at
~/bin/arc(optional but recommended) - For DataHUB sync: Personal Access Token for git.nfdi4plants.org or datahub.hhu.de
Interactive ARC Creation Workflow
Guide the user through these phases in order. Ask questions conversationally — don't dump all questions at once. Batch 2-4 related questions per message.
Phase 1: Investigation Setup
Ask the user:
- Investigation identifier (short, lowercase-hyphenated, e.g.
cold-stress-arabidopsis) - Title (concise name for the investigation)
- Description (textual description of the research goals)
- Where to store the ARC locally (suggest
/home/uranus/arc-projects/\x3Cidentifier>/)
Then run scripts/create_arc.sh \x3Cpath> \x3Cidentifier> and set investigation metadata via:
arc investigation update -i "\x3Cid>" --title "\x3Ctitle>" --description "\x3Cdesc>"
Phase 2: Studies
For each study, ask:
- Study identifier (e.g.
plant-growth) - Title and description
- Organism (for Characteristic [Organism])
- Growth conditions (temperature, light, medium, etc.)
- Source materials (what goes in — seeds, cell lines, etc.)
- Sample materials (what comes out — leaves, roots, extracts, etc.)
- Protocols — does the user have protocol documents to include?
- Factors — what experimental variables are being tested? (e.g., temperature, genotype, treatment)
Create with:
arc study init --studyidentifier "\x3Cid>"
arc study update --studyidentifier "\x3Cid>" --title "\x3Ctitle>" --description "\x3Cdesc>"
Copy protocol files to studies/\x3Cid>/protocols/.
Copy resource files to studies/\x3Cid>/resources/.
Phase 3: Assays
For each assay, ask:
- Assay identifier (e.g.
proteomics-ms,rnaseq,sugar-measurement) - Measurement type (e.g., protein expression profiling, transcription profiling, metabolite profiling)
- Technology type (e.g., mass spectrometry, nucleotide sequencing, plate reader)
- Technology platform (e.g., Illumina NovaSeq, Bruker timsTOF)
- Data files — where are the raw data files? (will go into
assays/\x3Cid>/dataset/) - Processed data — any processed output files?
- Protocols — assay-specific protocols?
- Performers — who performed this assay? (name, affiliation, role)
Create with:
arc assay init -a "\x3Cid>" --measurementtype "\x3Ctype>" --technologytype "\x3Ctech>"
Copy data to assays/\x3Cid>/dataset/, protocols to assays/\x3Cid>/protocols/.
Phase 4: Workflows (optional)
Ask if there are computational analysis steps. For each:
- Workflow identifier (e.g.
deseq2-analysis,heatmap-generation) - Description of what it does
- Code files (scripts, notebooks)
- Dependencies (Python packages, R libraries, Docker image)
Place code in workflows/\x3Cid>/.
Note: workflow.cwl is REQUIRED by spec but often created later. Inform user.
Phase 5: Runs (optional)
Ask if there are computation outputs. For each:
- Run identifier
- Which workflow produced it
- Output files (figures, tables, processed data)
Place outputs in runs/\x3Cid>/.
Phase 6: Contacts & Publications
Ask:
- Investigation contacts (name, email, affiliation, role — at minimum the PI)
- Publications (if any — DOI, PubMed ID, title, authors)
Add via:
arc investigation person register --lastname "\x3Clast>" --firstname "\x3Cfirst>" --email "\x3Cemail>" --affiliation "\x3Caff>"
Phase 7: Git Commit & DataHUB Sync
- Configure git user:
git config user.name "\x3Cname>"
git config user.email "\x3Cemail>"
- Commit:
git add -A
git commit -m "Initial ARC: \x3Cinvestigation title>"
- Ask if the user wants to push to a DataHUB. If yes:
- Ask which host (git.nfdi4plants.org, datahub.hhu.de, etc.)
- Create remote repo (via browser or API)
- Set remote and push
ISA Metadata Reference
For detailed ISA-XLSX fields, annotation table columns, and ontology references, read references/arc-spec.md.
Key Reminders
- Assay data is immutable — never modify files in
assays/\x3Cid>/dataset/after initial placement - Studies describe materials, assays describe measurements
- Workflows are code, runs are outputs
- Git LFS for files > 100 MB:
git lfs track "*.fastq.gz" "*.bam" "*.raw" - Don't store ARCs on OneDrive/Dropbox — Git + cloud sync causes conflicts
- ARC Commander CLI reference:
arc \x3Csubcommand> --help
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install arc-creator - 安装完成后,直接呼叫该 Skill 的名称或使用
/arc-creator触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
ARC Creator 是什么?
Create and populate Annotated Research Contexts (ARCs) following the nfdi4plants ARC specification. Use when creating a new ARC, adding studies/assays/workflows/runs, annotating ISA metadata, organizing research data into ARC structure, or pushing ARCs to a DataHUB. Guides the user interactively through all required and optional metadata fields. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1063 次。
如何安装 ARC Creator?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install arc-creator」即可一键安装,无需额外配置。
ARC Creator 是免费的吗?
是的,ARC Creator 完全免费(开源免费),可自由下载、安装和使用。
ARC Creator 支持哪些平台?
ARC Creator 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 ARC Creator?
由 IngoGiebel(@ingogiebel)开发并维护,当前版本 v1.0.0。