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 Nero1688/claude-academic-skills --skill reproducibility-architectgit clone --depth 1 https://github.com/Nero1688/claude-academic-skillsWrote 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/nero1688/claude-academic-skills/reproducibility-architect)<a href="https://agentmods.dev/skills/nero1688/claude-academic-skills/reproducibility-architect"><img src="https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/reproducibility-architect/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/nero1688/claude-academic-skills/reproducibility-architect"><img src="https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/reproducibility-architect.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 | $0.00521 | $0.02854 |
| Opus 5.5 | $0.00208 | $0.01142 |
| Sonnet 5.5 | $0.00104 | $0.00571 |
| Haiku 4.5 | $0.00052 | $0.00285 |
Grade A, and why
reproducibility-architect 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 7d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
可重現性與複製包架構師(Reproducibility Architect)
Step 1|可重現的專案結構(地基)
固定骨架,讓 replicator 一眼看懂:
project/
├── README.md # replicator 指南(見 Step 5)
├── run_all.R / run_all.py # master script:一鍵從 raw 跑到 output
├── renv.lock / requirements.txt # 環境鎖定
├── data/
│ ├── raw/ # 原始資料,唯讀,絕不被程式改寫
│ └── derived/ # 程式產生的中間檔(可由 raw 重建,不進版本庫)
├── code/
│ ├── 01_clean.R
│ ├── 02_integrate.R # 多源整合(接 multi-source-data-integrator)
│ ├── 03_analysis.R
│ └── 04_tables_figures.R
└── output/
├── tables/ # 每個檔對應論文某表
└── figures/ # 每個檔對應論文某圖
鐵律:raw 唯讀(所有清理輸出到 derived);輸出檔名對應論文表號圖號 (reviewer 追得到「表 4 是哪支程式產的」);master script 按序呼叫,中途不需手動介入。
Step 2|計算環境捕捉(別人跑得出來的關鍵)
- R:
renv::init()→renv::snapshot()產renv.lock(鎖定套件版本); replicatorrenv::restore()還原。 - Python:
pip freeze > requirements.txt或 condaenvironment.yml; 進階用 Docker 鎖 OS 層(頂刊複製包漸增)。 - 亂數種子:所有 bootstrap/模擬/隨機分派設固定 seed,寫在 master script 開頭。
- 版本聲明:R/Python 版本、作業系統、關鍵套件版本寫進 README—— 計量套件(如 did、fixest)更新可能改變結果,版本是可重現的一部分。
- 路徑:一律相對路徑(用 here::here / Path);絕不硬編本機絕對路徑 (別人的電腦沒有你家目錄的絕對路徑)。
Step 2b|可重現報告層:Quarto(把「程式→表圖→文字」縫成一份可重跑的原始檔)
複製包能重跑出表圖只是一半;頂刊資料編輯越來越常問「稿件裡的數字是從哪個輸出貼過來的」。 Quarto(.qmd)讓程式、圖表與正文住在同一份原始檔,render 時重算——論文裡的每個數字都有 可回溯的程式碼塊,直接消滅手動搬數字的貼錯風險。
- 何時用:投稿要交複製包且稿件含大量表圖;或審稿要求「換一個設定重跑全部結果」。 不用:純理論稿、或期刊只收 Word 且你已有穩定的表格直出流程(r-spss 的 modelsummary→docx)。
- 最小結構:
paper.qmd(正文+程式碼塊)+_quarto.yml(輸出格式、execute: freeze: auto凍結已算結果避免每次全跑)+references.bib。表格用gt/modelsummary、圖用ggplot2, 全部在程式碼塊內產生,不貼外部圖片。 - 輸出 Word 給期刊:
format: docx搭reference-doc: template.docx——模板裡先把正文樣式設好 中文標楷體、英數 Times New Roman(本家族字型紀律),render 出來的 docx 才會合規; 交付前仍照 D 檔第 5 節跑字型掃描,不因為是 Quarto 產的就免驗。 - 從 R Markdown/bookdown/xaringan 遷移:
quarto convert old.Rmd起手,YAML 與 chunk 選項語法 有差(#| echo: false取代{r, echo=FALSE}),遷移邏輯與官方 R 套件慣例以 posit-dev/skills 為權威來源(見ATTRIBUTION.md),本技能不重製其內容。 - 與 Step 1/2 的關係:
.qmd是 master script 的「敘事層」,環境仍由 renv 鎖;quarto render應能在乾淨環境從raw/一路跑到成品,否則它只是漂亮的筆記本、不是複製包。
What ships with it
2 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.
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.
- 7d ago Changed 34180c6a444e
- 1mo ago Changed · +21 lines · -85 tokens per session 46e67254992a
- 1mo ago First seen · 94 lines · 606 tokens per session scan A 6c9ec5d9f32a
reproducibility-architect is a skill published in the GitHub repository Nero1688/claude-academic-skills (13 stars, last pushed 5d ago), licensed MIT. It adds 521 tokens to every session and 2,854 once invoked, about $0.0021 per session on Opus 5.5. 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.
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