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Math Progress Monitor

CommunityPopular
parcadei
math-progress-monitor

Metacognitive check-ins during problem solving - detects when to pivot or persist

Overview

Publisherparcadei
RepositoryContinuous-Claude-v3
Skill namemath-progress-monitor
Stars
3.9K
Forks
303
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by parcadei on GitHub. Read the source before you install it.

Installation

Install the Math Progress Monitor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/math/math-progress-monitor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git /tmp/Continuous-Claude-v3
mkdir -p .claude/skills
cp -r /tmp/Continuous-Claude-v3/.claude/skills/math/math-progress-monitor .claude/skills/math-progress-monitor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Math Progress Monitor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Math Progress Monitor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Math Progress Monitor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Frequently asked questions

What does the Math Progress Monitor AI skill do?

Metacognitive check-ins during problem solving - detects when to pivot or persist

Why use Math Progress Monitor on TypingMind?

Because you install it once and use it with any model. Math Progress Monitor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Math Progress Monitor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/math/math-progress-monitor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Math Progress Monitor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Math Progress Monitor?

As many as you like. As long as a model supports skills, you can use Math Progress Monitor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Math Progress Monitor AI skill free?

Yes. It is published on GitHub by parcadei under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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