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]

|

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

安装

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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)