File: workshop/05-agentic-workflows-intro.md
Overall Score: 5.43 / 10.0 (corpus mean: 6.14)
Flagged Dimensions:
| Dimension |
Score |
Benchmark |
Delta |
| cognitive_load |
8.5 |
≤ 800 words |
-0.8 (1,107 words, over by ~300) |
| active_learning |
2.4 |
activity density ≥ 3 (0.72 measured) |
-7.6 |
Root Cause (≤ 2 sentences):
Despite having three labeled "Activity" sections (identify the parts, agentic-or-standard, write a task brief), the page only contains 2 code blocks and 6 checklist items against 1,107 words, so measured activity density (0.72) is far below the 3.0 benchmark — the "activities" are mostly read-and-reveal <details> prompts rather than code blocks or checklist-verifiable actions the rubric counts. The word count also exceeds the 800-word ideal by roughly 300 words, compounding the cognitive-load penalty.
Evidence (quoted from the file):
Activity 1 — identify the parts: Open any .lock.yml file in your repo and find the on: key. That is the compiled trigger that came from your frontmatter.
# Example: open .github/workflows/my-workflow.lock.yml
# Find the "on:" key — that is your compiled trigger.
Learning Science Rationale:
Mayer's active-processing principle expects generative activities to require an artifact or checkable output, not just a reveal-the-answer <details> toggle; the rubric's activity_density metric (code blocks + checklist items per 100 words) reflects this by only counting verifiable artifacts. Converting one or two of the three "Activities" into short checklist items with concrete, checkable sub-steps (e.g., "- [ ] I found the on: key and wrote down its value") would both raise the measured activity density and give learners a genuine retrieval-practice moment consistent with generative-learning theory.
Improvement Prompt (for an agent):
Edit workshop/05-agentic-workflows-intro.md to raise activity_density above 3.0 and trim
word count toward 800. First, convert "Activity 1 — identify the parts" and "Activity 3 —
write a task brief" into short checklist-style sub-steps (2-3 "- [ ] ..." items each)
instead of prose-only instructions, so the rubric's checklist_items count increases.
Second, trim the "Three key terms" table's descriptive prose and the "Why This Matters"
paragraph by combining redundant sentences (target removing ~250-300 words total) without
losing the trigger/task-brief/safe-outputs definitions. Keep the existing two code blocks
and the final :white_check_mark: Checkpoint section unchanged. Run
npx --yes markdownlint-cli2 "**/*.md" after editing and confirm the file still reads
coherently end-to-end.
Expected Score After Fix: 6.7 / 10.0
Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · 96.3 AIC · ⌖ 12.2 AIC · ⊞ 9.5K · ◷
File:
workshop/05-agentic-workflows-intro.mdOverall Score:
5.43 / 10.0(corpus mean:6.14)Flagged Dimensions:
Root Cause (≤ 2 sentences):
Despite having three labeled "Activity" sections (identify the parts, agentic-or-standard, write a task brief), the page only contains 2 code blocks and 6 checklist items against 1,107 words, so measured activity density (0.72) is far below the 3.0 benchmark — the "activities" are mostly read-and-reveal
<details>prompts rather than code blocks or checklist-verifiable actions the rubric counts. The word count also exceeds the 800-word ideal by roughly 300 words, compounding the cognitive-load penalty.Evidence (quoted from the file):
Learning Science Rationale:
Mayer's active-processing principle expects generative activities to require an artifact or checkable output, not just a reveal-the-answer
<details>toggle; the rubric's activity_density metric (code blocks + checklist items per 100 words) reflects this by only counting verifiable artifacts. Converting one or two of the three "Activities" into short checklist items with concrete, checkable sub-steps (e.g., "- [ ] I found theon:key and wrote down its value") would both raise the measured activity density and give learners a genuine retrieval-practice moment consistent with generative-learning theory.Improvement Prompt (for an agent):
Expected Score After Fix:
6.7 / 10.0