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[curriculum-eval] side-quest-11-06-anthropic-key.md: active_learning — mostly passive procedural steps, low activity density

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評価

難易度
1/5
見積もり時間
1〜3時間
初心者へのやさしさ
92/100
issue の種類
ドキュメント
明瞭さ
明確に書かれている
活発さ
活発
技術スタック
markdown
領域
documentation

調査の方向性

workshop/side-quest-11-06-anthropic-key.md を開き、既存の Common mistakes の詳細ブロックと Compile your workflow セクションを確認してください。指定された余分な太字だけを削除し、既存の内容を維持したまま検証マイクロタスクを追加してから、npx --yes markdownlint-cli2 "workshop/side-quest-11-06-anthropic-key.md" を実行し、追加によって発生した lint エラーを修正してください。

索引モデルが issue の本文から書いたものです。

説明

curriculum documentation quality

File: workshop/side-quest-11-06-anthropic-key.md
Overall Score: 5.39 / 10.0 (corpus mean: 6.09 / 10.0)

Flagged Dimensions:

Dimension Score Benchmark Delta
cognitive_load 7.2 10.0 (≤ 15 new concepts) -2.8 (26 new concepts, 11 over ideal)
active_learning 3.5 10.0 (density ≥ 3) -6.5

Root Cause (≤ 2 sentences):
This short 665-word setup guide introduces 26 distinct bolded/code-formatted terms (ANTHROPIC_API_KEY, engine: claude, api.anthropic.com, network.allowed, copilot-requests: write, multiple UI-path terms, common-mistakes list items, etc.) — nearly double the 15-concept ideal for its length — packed into procedural steps, secret-naming rules, and a common-mistakes list, each of which reads as a new concept to the rubric's bold/code scan. Activity density (1.05) is well below 3.0 because the page is mostly sequential prose instructions with only one real code block plus 5 checklist items.

Evidence (quoted from the file):

"Wrong name: any variation (anthropic_api_key, ANTHROPIC-API-KEY, CLAUDE_API_KEY) will cause a silent auth failure." ... "Copied with extra whitespace: pasting from some tools adds a leading space." ... "Closed the Anthropic tab before saving: you cannot retrieve the key again." — three bolded pitfall labels plus four inline-code secret-name variants in one bullet list.

Learning Science Rationale:
Cognitive Load Theory suggests that a procedural how-to page should minimize extraneous load from listing every possible failure mode inline; segmenting common mistakes into a clearly-labeled troubleshooting aside (already partially done via <details>) rather than bolding each as if it were a new taught concept would reduce the rubric's counted concept load without losing content. The page's Apply-level task (configuring a secret and editing frontmatter) is appropriate for a side quest, but it would benefit from a verification-based Apply activity, e.g., asking the learner to intentionally test the wrong name to see the failure, per active-recall principles in cognitive load research.

Improvement Prompt (for an agent):

Edit workshop/side-quest-11-06-anthropic-key.md to reduce counted concept density and raise
activity density:

1. In the existing "Common mistakes with this secret" <details> block, remove bold
   formatting from the four wrong-name code variants (anthropic_api_key, ANTHROPIC-API-KEY,
   CLAUDE_API_KEY) — list them as plain inline code without individually bolding the
   preceding label words, so they read as one troubleshooting list rather than four new
   taught concepts.

2. Add one short verification micro-task right after the "Compile your workflow" section:
   ask the learner to run `gh aw compile` once with a deliberately misnamed secret (or the
   secret temporarily removed) to see the expected failure message, then restore the correct
   secret and re-run. Wrap the expected failure text in a fenced code block so it also counts
   toward activity density.

3. Keep the existing Checkpoint section, the frontmatter example, and the "Common mistakes"
   content itself unchanged in substance — only remove excess bolding and add the one
   verification step.

4. Run `npx --yes markdownlint-cli2 "workshop/side-quest-11-06-anthropic-key.md"` and fix any
   lint errors introduced.

Expected Score After Fix: 6.2 / 10.0 (fewer counted concepts from de-bolded troubleshooting list, plus one added verification activity raising active_learning).

Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · 90.7 AIC · ⌖ 21.1 AIC · ⊞ 9K · ◷

  • expires on Sep 26, 2026, 7:53 AM UTC
主要言語
JavaScript
スター
49
フォーク
20
平均マージ
9時間 44分
マージ済み PR（30日）
25

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