Content Refiner (The Fixer)

Purpose

POST-GATE TOOL. Transforms content that FAILED Gate 4 into passing content. Focuses on trimming verbosity and fixing continuity.

When to Use

Trigger: Gate 4 (Acceptance Auditor) returned [FAIL].
Goal: Fix word count OR continuity issues (or both).
Key: Diagnose what failed BEFORE applying fixes.

CRITICAL: Pre-Refinement Diagnosis

DO NOT apply fixes blindly. Gate 4 fails for different reasons requiring different strategies.

Step 0: Identify What Failed (Mandatory)

Ask the user OR examine the Gate 4 failure message:

Failure Type	Question	Action
Word Count	"Is the lesson over the target (typically 1500 words)?"	Calculate exact % to cut
Continuity	"Does the opening reference the previous lesson?"	Rewrite opening only
Both	"Word count AND continuity broken?"	Two-phase approach

DIAGNOSIS EXAMPLES:

Example 1: Word Count Only

Content: 1950 words, Target: 1500
Excess: 450 words
% to cut: (450 / 1950) × 100 = 23%
→ CUT EXACTLY 23%, not generic 15-20%

Example 2: Continuity Only

Opening: "Let's explore this new topic..."
Problem: Doesn't reference Lesson N-1
→ Rewrite opening only; don't cut words

Example 3: Both

Word count: 1950 (23% over)
Opening: Generic, missing prior lesson reference
→ Phase 1: Rewrite opening (identify anchor from Lesson N-1)
→ Phase 2: Cut words to 23% (context-aware)

Step 1: Assess Content Layer (Context-Aware Cutting)

Read the lesson's frontmatter to determine layer:

Layer	Cutting Strategy
L1 (Manual)	Keep foundational explanations; cut elaboration
L2 (AI-Collaboration)	Keep Try With AI sections (core); cut narrative padding
L3 (Intelligence)	Keep pattern insights; cut explanatory scaffolding
L4 (Spec-Driven)	Keep specification details; cut conceptual scaffolding

The Refinement Procedure (Layer-Aware)

Phase 1: The Connection Builder (Continuity Fix)

Do this FIRST if opening is generic.

Formula:

In [Previous Lesson], you [SPECIFIC OUTCOME from Lesson N-1].
Now, we will [CONNECT outcome to new goal] by [STRATEGY].

Validation:

Opening references Lesson N-1 by name
Specific outcome (not generic "learned about...")
Clear connection shows why this lesson matters (builds on N-1)

After fixing: Proceed to Fluff Cutter if word count also fails.

Phase 2: The Fluff Cutter (Word Count Fix)

Apply layer-specific cuts in this order:

FOR ALL LAYERS:

Delete redundant "Why This Matters" sections
- Keep ONLY if it reveals non-obvious insight
- If same point made in text AND in "Why This Matters" → delete WTM
Merge repeated examples
- Find duplicate explanations
- Keep first, delete second
Tighten transitions between sections
- Replace "As we discussed earlier, X..." with direct reference

FOR L1-L2 ONLY (students still building foundation): 4. Reduce "Try With AI" sections to exactly 2 prompts

Keep foundational + one advanced
Delete exploratory extras

Keep educational scaffolding (explanations, examples)

FOR L3-L4 ONLY (students ready for advanced patterns): 4. Trim narrative scaffolding

Keep pattern insights and rules
Delete "why this matters philosophically"

Remove beginner-level explanations
- Assume students understand fundamentals

FOR ALL LAYERS: 6. One Analogy Rule: Keep the BEST analogy for the concept; delete redundant ones 7. Merge Tables/Text: Use ONE format (table OR prose), never both 8. Reduce Examples: Keep 2-3 best; delete "also consider..." 9. Tighten Lists: Convert 5-item lists to 3 core items

Verification:

Word count after cuts: [TARGET ± 5%]
No L1 content cut from L1 lessons
No pattern insights lost from L3-L4 lessons
Try With AI: 2 prompts if L1-L2, keep all if L3-L4

Phase 3: Post-Refinement Validation (CRITICAL)

After applying fixes, verify the content now PASSES Gate 4:

✓ Word Count Check:
  Current: [X] words
  Target: [target_from_spec]
  Status: [PASS if ≤target ± 5%, FAIL if over]

✓ Continuity Check:
  Opening references Lesson [N-1]? [YES/NO]
  Specific outcome mentioned? [YES/NO]
  Connection to new lesson clear? [YES/NO]

✓ Layer Appropriateness:
  No foundational cuts from L1-L2? [YES/NO]
  No pattern insight loss from L3-L4? [YES/NO]

✓ Content Integrity:
  Removed examples still explained elsewhere? [YES/NO]
  Cut sections non-essential? [YES/NO]

NEXT STEP RECOMMENDATION:

"Refined content is ready.

Word count: [after] (target: ≤[target])
Continuity: Now references Lesson [N-1]

Recommend re-submitting to acceptance-auditor for Gate 4 re-validation.
Command: [provide re-validation instruction]"

Output Format

## Refinement Report: [Lesson Name]

### Diagnosis
**Issue Found**: [Word count | Continuity | Both]
**Layer**: [L1/L2/L3/L4]

### Metrics
| Metric | Before | After | Target | Status |
|--------|--------|-------|--------|--------|
| Word Count | 1950 | 1485 | ≤1500 | ✅ PASS |
| Continuity | Generic opening | References Lesson 2 | Specific reference | ✅ PASS |

### Fixes Applied
1. **Phase 1**: Rewrote opening to reference "booking-agent implementation" from Lesson 2
2. **Phase 2**: Deleted 240 words using layer-aware cuts:
   - Removed redundant "Why This Matters" section (line 45, 120 words)
   - Merged duplicate example (lines 67-89, 85 words)
   - Cut 1 extra "Try With AI" prompt (35 words)
3. **Phase 3**: Validated word count and continuity

### Ready for Re-validation
✅ Word count: 1485 (≤1500)
✅ Continuity: Opening references Lesson 2
✅ Layer integrity: All L2 AI examples preserved

**Next**: Re-submit to acceptance-auditor for Gate 4 validation

### Refined Content
[Full refined lesson content]

content-refiner