math-progress-monitor
Metacognitive check-ins during problem solving - detects when to pivot or persist
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install parcadei-continuous-claude-v3-math-progress-monitor
Repository
Skill path: .claude/skills/math/math-progress-monitor
Metacognitive check-ins during problem solving - detects when to pivot or persist
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: parcadei.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install math-progress-monitor into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/parcadei/Continuous-Claude-v3 before adding math-progress-monitor to shared team environments
- Use math-progress-monitor for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: math-progress-monitor description: Metacognitive check-ins during problem solving - detects when to pivot or persist --- # 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 1. What have you tried? (inventory) 2. What did you learn? (extract) 3. Is it getting simpler or harder? (complexity) 4. Can you check a piece? (verify) 5. What's the smallest step? (decompose) 6. 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