[curriculum-eval] curriculum_assessment.py: checkpoint_quality — regex misses `:white_check_mark:` so 92/94 pages score 0
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 76/100
- Issue type
- Bug
- Clarity
- Clearly specified
- Activity status
- Active
- Tech stack
- github-actions, markdown, python
- Domain
- devtools, testing-qa
Research direction
Start with .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py, especially CHECKPOINT_RE, and inspect the emoji based scaffolding regexes mentioned in the issue. Read the assessment tests, if present, then run the assessment over workshop/*.md and check workshop/04-github-actions-intro.md. Done when the checkpoint is detected in that page and the assessment no longer reports a false missing checkpoint.
Written by the indexing model from the issue text.
Description
File: .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py
Overall Score: n/a (affects all pages; corpus mean 6.06, ceiling suppressed by ~2.0 × 10 / 10.0 = ~2.0 points)
Flagged Dimensions:
| Dimension | Score | Benchmark | Delta |
|---|---|---|---|
| checkpoint_quality | 0.0 (92 of 94 pages) | ≥ 4 items → 10.0 | −10.0 |
| scaffolding | 5.0 on most pages (to verify) | section present → 10.0 | −5.0 |
Root Cause (≤ 2 sentences):
CHECKPOINT_RE = r"##\s+✅\s*Checkpoint" requires the literal emoji, but the workshop (per AGENTS.md) writes ## :white_check_mark: Checkpoint. Pages such as 04-github-actions-intro.md (5 checklist items) and 05-agentic-workflows-intro.md therefore get has_checkpoint = false and a bogus missing_checkpoint finding.
Evidence (quoted from the file):
CHECKPOINT_RE = re.compile(r"##\s+✅\s*Checkpoint", re.IGNORECASE)vs.workshop/04-github-actions-intro.md:138:## :white_check_mark: Checkpoint
Learning Science Rationale:
Valid measurement is a precondition for acting on any rubric: if a metric is blind to the content's actual markup, it produces false positives that send authors to fix non-problems (checkpoints already support retrieval practice and self-assessment, per formative-assessment research). Fixing the detector restores signal for the real weaknesses: concept overload, length, and low activity density.
Improvement Prompt (for an agent):
In .github/skills/curriculum-quantitative-assessment/curriculum_assessment.py, update CHECKPOINT_RE to accept both the emoji and the GitHub shortcode, e.g. r"##\s+(?:✅|:white_check_mark:)\s*Checkpoint". Also check the "Before You Start"/"Prerequisites" scaffolding regex (":clipboard:" vs 📋) and any other emoji-based regexes for the same mismatch, and make them accept both forms. Add/adjust tests if present, re-run the assessment over workshop/*.md, and confirm has_checkpoint is true for workshop/04-github-actions-intro.md and that the corpus mean score rises accordingly. Do not edit workshop content.
Expected Score After Fix: ~7.8 / 10.0 corpus mean (checkpoint dimension recovers up to +2.0 weighted points on pages with ≥4 items; scaffolding gains if also affected).
Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · ~37 AIC · ⌖ ~1 AIC · ⊞ 5K · ◷
- expires on Nov 6, 2026, 3:04 AM UTC
- Dominant language
- JavaScript
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- 58
- Forks
- 40
- Avg merge
- 4d 4h
- Merged PRs (30d)
- 8
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