SuperAPI AI Directory

tech-article-reproducibility

Writing & research

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Updated 10-15 21:51

About this skill

Tech Article Reproducibility

Measure the quality of a technical article from the perspective of "whether readers can reproduce the same thing on their own." This is a separate axis independent of style evaluation (mizchi-blog-style) and logical evaluation.The most important thing in a technical article is whether the reader who read it can reproduce it on their own It stands on this premise.

When to use it

  • Final check before publishing a technical article draft
  • Hands-on articles / tutorial articles
  • Tool introduction articles / setup articles
  • Verification of articles that claim "it worked"

Situations not to use it:

  • Concept explanation articles (there is nothing to reproduce)
  • Poems / opinion articles
  • Small tips that are self-contained within the article

Reproducibility check perspectives (10 axes)

Score each axis from 0 to 2 points, total 20 points maximum → converted to 10 points.

# Axis 0 (NG) 1 (partial) 2 (OK)
1 Explicitness of environment prerequisites No OS / version / required tools listed Partially listed All listed (OS, lang version, CLI tools)
2 Completeness of code Fragments only, import/setup omitted Main parts only Complete form that works by copy-paste
3 Accuracy of commands left as placeholder (<your-token> etc. with no explanation) Some placeholders Executable as-is
4 Explicitness of version dependencies No mention Partial Explicitly states e.g. "works with v3.x", "v2 and earlier is X"
5 Full posting of config files Excerpts only Main keys only Full minimal working configuration
6 Presentation of expected output none Explained in prose Actual output / screenshots
7 Handling of errors Not addressed Mentions 1 case Several major errors + handling
8 Explicitness of project prerequisites Author's environment prerequisites are implicit Partially explicit path / repo structure / existing settings all explicit
9 Link health Broken links or authentication required Some require authentication All public and accessible
10 Explicitness of author-dependent knowledge Helpers / dotfiles implicit Partially explicit All explicit or unnecessary

Evaluation workflow

Use the same subagent dispatch as empirical-prompt-tuning to evaluate technical articles. The difference is that the subagent is given not the role of an "implementer" but the role-play of "a first-time reader attempting to reproduce it" to be made to do.

  1. Finalize the target article
  2. subagent dispatch (template described below)
  3. Extract "reproduction stumbling points" from the returned evaluation
  4. Add / revise the descriptions in the article corresponding to the stumbling points
  5. If necessary, re-evaluate with a new subagent

subagent dispatch template

あなたは <記事のテーマ領域> に興味があるが <技術スタック> は初めての読者です。
この記事を読んで、手元の環境で同じことを再現しようとします。

## 対象記事
<記事ファイルのパス>

## 評価観点 (再現性 10 軸)
各軸を 0〜2 点で採点。`tech-article-reproducibility` skill の判定表参照:
/Users/mz/.claude/skills/tech-article-reproducibility/SKILL.md

1. 環境前提の明示
2. コードの完全性
3. コマンドの正確性
4. バージョン依存の明示
5. 設定ファイル全文掲載
6. 期待される出力の提示
7. エラー時の対処
8. プロジェクト前提の明示
9. リンク健全性 (実際に WebFetch で確認)
10. 著者依存知識の明示

## タスク
1. 記事を読みながら「自分が手元で再現するならどこで詰まるか」を想像する
2. 各軸 0〜2 で採点 + 根拠を引用
3. 詰まりポイント Top 5 を行番号付きで列挙

## レポート構造
- 再現性スコア: X/20 (内訳テーブル)
- 詰まりポイント Top 5: <行番号> <引用> → <なぜ詰まるか>
- 不足情報: 記事に追加すべき情報のリスト
- 総評: この記事を読んで手元で再現できる確率は何 % か (主観)

How to read the score

  • 18-20: Publishable as a hands-on, almost no additional information needed
  • 14-17: Requires some googling but is reproducible, publishable
  • 10-13: Requires information outside the article to reproduce, additional revisions recommended
  • 9 or below: Difficult to reproduce, reconsider the article's premises or position it as something other than a hands-on

Pitfalls

  • The evaluator's prior knowledge is too advanced: If you don't explicitly give the subagent an "beginner role," it will judge from an expert's perspective that it is "sufficient." Emphasize "first-time" in the prompt
  • Ignoring link health: A link may be alive at publication time but break a year later.Alive Separately check whether reproduction is possible using only links
  • Inlining all sample code: Reproducibility improves, but the article becomes bloated. A hybrid approach combining this with links to a repository is realistic
  • Reproducibility ≠ writing quality: There are articles that are highly reproducible but hard to read.mizchi-blog-style Use in combination with etc. to measure on both axes

Related

  • empirical-prompt-tuning — the meta-skill of subagent dispatch + iterative improvement
  • mizchi-blog-style — evaluation on the writing-style axis (an axis independent of this skill)