Continuous-Claude-v3 math-progress-monitor
Metacognitive check-ins during problem solving - detects when to pivot or persist
install
source · Clone the upstream repo
git clone https://github.com/parcadei/Continuous-Claude-v3
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/parcadei/Continuous-Claude-v3 "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/math/math-progress-monitor" ~/.claude/skills/parcadei-continuous-claude-v3-math-progress-monitor && rm -rf "$T"
manifest:
.claude/skills/math/math-progress-monitor/SKILL.mdsource content
Math Progress Monitor
When to Use
Trigger on phrases like:
- "am I on the right track"
- "is this approach working"
- "I'm stuck"
- "should I try something else"
- "verify my progress"
- "check my reasoning"
- "is this getting too complicated"
Use mid-work to assess whether to continue, pivot, or decompose (Schoenfeld's metacognitive control).
Process
Run a structured progress assessment:
1. Inventory attempts
Ask: "What have you tried so far?"
- List each approach
- Order by when attempted
- Note time spent
2. Extract learnings
Ask: "What did each attempt tell you?"
- Even failures provide information
- What was ruled out?
- What patterns emerged?
3. Complexity check
Ask: "Is complexity growing faster than expected?"
- Warning signs:
- More terms than you started with
- New variables appearing
- Calculation getting messier
- Normal: complexity stays flat or decreases
4. Spot-check verification
Ask: "Can you verify any intermediate results?"
- Run numerical examples
- Check limiting cases
- Dimensional analysis
5. Decomposition check
Ask: "Is there a simpler sub-problem to solve first?"
- Identify dependencies
- Find stepping stones
- Reduce scope
6. Sunk cost assessment
Ask: "What would abandoning this approach cost?"
- Time already spent (irrelevant)
- Insights that transfer (relevant)
- Probability of success if continue
Key Questions to Ask
- What have you tried? (inventory)
- What did you learn? (extract)
- Is it getting simpler or harder? (complexity)
- Can you check a piece? (verify)
- What's the smallest step? (decompose)
- Should you pivot? (decide)
Output Format
Progress Assessment: Status: [On track / Hitting resistance / Should pivot] Attempts Summary: 1. [Approach] -> [Outcome/Learning] 2. [Approach] -> [Outcome/Learning] Complexity Check: - Expected: [what should this look like] - Actual: [what it actually looks like] - Verdict: [Normal / Warning / Abandon] Verification Points: - [Intermediate result to check] - [Numerical test case] Recommendation: [Continue / Modify approach / Switch strategy / Decompose / Get more info] If Pivoting: - Alternative: [specific new approach] - Why it might work: [reasoning]
Example Interaction
User: I've been trying to evaluate this integral for an hour Claude: Let's do a progress check. Q1: What have you tried? > u-substitution with u = sin(x), then integration by parts twice. Q2: What did each tell you? > Substitution made it longer. Parts created a cycle. Q3: Complexity now vs start? > Much worse. Started with 3 terms, now have 8. Complexity Check: - Expected: Should simplify or stay similar - Actual: 3 terms -> 8 terms after 2 techniques - Verdict: WARNING - likely wrong approach Let me verify an intermediate step... [Runs sympy on original integral] This integral has closed form using: - Beta function (special function) - Or contour integration Recommendation: PIVOT Your algebraic approaches won't simplify this pattern. Alternative Approach: 1. Recognize: integral of sin^m(x) * cos^n(x) 2. Use Beta function identity 3. Or convert to complex exponentials Related Skills: - complex-analysis/contour-integrals - numerical-methods/numerical-integration Would you like the Beta function approach, or get a numerical answer first to verify?
Co-activates
When user is stuck, suggest:
- math-intuition-builder - reset understanding
- math-model-selector - if framework was wrong
- math-mode - for verification computations
- Relevant domain skill - for alternative approach