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[curriculum-eval] .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py: checkpoint_quality, scaffolding — regex misses emoji

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Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
86/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Attiva
Stack tecnologico
python
Ambito
testing-qa, tooling

Direzione di ricerca

Inizia in .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py leggendo CHECKPOINT_RE e la logica di has_prereq_section in collect_metrics_from_text. Esegui nuovamente la rubrica su workshop/*.md e controlla a campione 04-github-actions-intro.md, 05-agentic-workflows-intro.md e side-quest-17-07-repo-poisoning.md; il lavoro è completato quando vengono rilevati sia i titoli con glifi emoji sia i titoli con shortcode, senza modificare altra logica di valutazione.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

curriculum documentation quality

File: .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py (corpus-wide impact: 90–93 of 93 workshop files)
Overall Score: N/A — systemic tooling defect, not a single-page score
Corpus Mean: 6.09 / 10.0 (artificially depressed by this bug)

Flagged Dimensions (aggregate impact):

Dimension Score (current) Benchmark Delta
checkpoint_quality 0.0 for 90/93 files 10.0 if ≥4 checklist items -10.0 (should be ~7.5–10 for most files)
scaffolding 5.0 for 93/93 files 10.0 if prereq/before-you-start section present -5.0 (should be 10.0 for ~86 files)

Root Cause (≤ 2 sentences):
CHECKPOINT_RE = re.compile(r"##\s+✅\s*Checkpoint", ...) and the prerequisite-section regex r"##\s+📋\s*Before You Start" only match literal emoji glyphs, but this workshop's actual convention (used on nearly every page) is GitHub-flavored Markdown emoji shortcodes: ## :white_check_mark: Checkpoint and ## :clipboard: Before You Start. Because the regexes never match the shortcode form, has_checkpoint is False for 90 of 93 files and has_prereq_section is False for all 93 files, even though the content is present and well-formed.

Evidence (quoted from the file):

workshop/04-github-actions-intro.md contains ## :clipboard: Before You Start and ## :white_check_mark: Checkpoint with 5 checklist items — yet rubric-results.json reports "has_checkpoint": false, "has_prereq_section": false, "checkpoint_quality": 0.0, "scaffolding": 5.0" for this file. The same pattern repeats for side-quest-17-07-repo-poisoning.md, side-quest-11-06-anthropic-key.md, 05-agentic-workflows-intro.md, and 86 other files.

Learning Science Rationale:
This is not a learning-science issue but a measurement-validity issue: per classical test theory, a rubric that systematically fails to detect a construct (checkpoints, scaffolding) it claims to measure produces scores with poor construct validity, making cross-file and cross-run comparisons (including the trend analysis in score-history.json) unreliable. Two of six weighted dimensions (weight 2.0 and 1.5 of 10.5 total, ≈33% of the composite) are affected, so this single defect can shift overall_score by roughly 0.5–1.1 points per file — enough to flip several files across the "below threshold" line used to select findings.

Improvement Prompt (for an agent):

In .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py, update the
regex patterns used to detect checkpoints and prerequisite sections so they also match
GitHub emoji-shortcode headings, not just literal emoji glyphs. Specifically:

1. Update CHECKPOINT_RE so it matches both:
   - "## ✅ Checkpoint" (literal emoji)
   - "## :white_check_mark: Checkpoint" (shortcode)
   Example: CHECKPOINT_RE = re.compile(
       r"##\s+(?:✅|:white_check_mark:)\s*Checkpoint", re.IGNORECASE)

2. Update the has_prereq_section detection in collect_metrics_from_text so it matches both:
   - "## 📋 Before You Start" (literal emoji)
   - "## :clipboard: Before You Start" (shortcode)
   - "## Prerequisites" (already handled)
   Example:
       re.search(r"##\s+(?:📋|:clipboard:)\s*Before You Start", raw, re.IGNORECASE)
       or re.search(r"##\s+Prerequisites", raw, re.IGNORECASE)

3. Re-run the rubric against workshop/*.md and confirm has_checkpoint and
   has_prereq_section now report True for files that use the :white_check_mark: and
   :clipboard: shortcode headings (spot-check 04-github-actions-intro.md,
   05-agentic-workflows-intro.md, and side-quest-17-07-repo-poisoning.md).

4. Do not change any other scoring logic, weights, or thresholds in this file.

Expected Score After Fix: Corpus mean rises from 6.09 / 10.0 toward an estimated 7.0–7.5 / 10.0, since ~90 files gain full scaffolding credit (5.0 → 10.0) and most gain checkpoint_quality credit (0.0 → 7.5–10.0 based on their existing 4+ checklist items.

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

  • expires on Sep 26, 2026, 7:53 AM UTC
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Merge medio
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