Self Improve logo

Self Improve

OrganizationPopular
ginlix-ai
self-improve

Report issues and propose fixes to improve your own capabilities when you encounter errors or limitations

Overview

Publisherginlix-ai
RepositoryLangAlpha
Skill nameself-improve
Stars
1.8K
Forks
288
Bundled files
Instructions only
LicenseApache-2.0
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 ginlix-ai on GitHub. Read the source before you install it.

Installation

Install the Self Improve 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.
  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/ginlix-ai/LangAlpha.git /tmp/LangAlpha
mkdir -p .claude/skills
cp -r /tmp/LangAlpha/plugins/langalpha_service/skills/self-improve .claude/skills/self-improve
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Self Improve 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 Self Improve 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 Self Improve 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.

Self-Improvement

You have access to gh CLI and git in the sandbox. Use this skill when you encounter bugs, errors, or limitations in your own capabilities during your work.

When to Activate This Skill

Recognize these situations during your normal work:

  • A tool call fails with an unexpected error
  • A skill's instructions (SKILL.md) have wrong examples or outdated API usage
  • An MCP tool returns malformed or unexpected data
  • A prompt instruction is unclear, contradictory, or missing
  • A sandbox script or package is broken or misconfigured
  • You notice a code pattern that would make your work more effective if fixed

Always ask the user for consent before filing an issue or creating a PR. Briefly explain what you found and what you want to report, then ask for approval. Do NOT file anything without explicit user confirmation.

Do NOT derail the user's current task. Keep the consent request brief, file the issue quickly after approval, then continue with the user's request.

Authentication

  • GITHUB_TOKEN env var is pre-configured (injected from GITHUB_BOT_TOKEN)
  • Git identity is set via env vars — no git config needed

Workflow 1: Report a Bug (default — quick, no cloning)

Use when: you encounter any issue with your own capabilities. Time: <30 seconds. Don't interrupt the user's flow.

Template:

bash
gh issue create --repo "ginlix-ai/LangAlpha" \
  --title "bug(agent): <what broke>" \
  --label "agent-reported" \
  --body "<structured body>"

Issue body structure:

## What I was doing
<user's task context — what were you trying to accomplish>

## What went wrong
<exact error message or unexpected behavior>

## Where the issue likely is
<file paths, function names, skill names — be specific>

## Suggested fix
<if obvious, describe; otherwise "Needs investigation">

## Environment
- Thread: <thread_id if available>
- Tool/Skill: <which tool or skill was involved>
- Error type: <tool_error | skill_instruction | mcp_data | prompt | sandbox>

@claude Please triage this issue — verify the root cause, assess severity, and suggest a fix if straightforward.

Workflow 2: Propose a Fix (rare — only when user explicitly asks)

Default to Workflow 1 (filing an issue). Only create a PR when the user explicitly asks you to fix it yourself. Do NOT propose PRs on your own initiative.

Steps:

  1. Clone or update: if .self-improve/langalpha exists, cd .self-improve/langalpha && git checkout main && git pull origin main to get latest. Otherwise gh repo clone "ginlix-ai/LangAlpha" .self-improve/langalpha -- --depth 1
  2. Branch: cd .self-improve/langalpha && git checkout main && git checkout -b bot/fix/<short-desc>
  3. Make the fix (keep it minimal and focused)
  4. Test: ruff check . && pytest (or relevant subset)
  5. Commit: conventional format — fix(scope): description
  6. PR:
bash
gh pr create --repo "ginlix-ai/LangAlpha" \
  --base main \
  --title "fix(agent): <what's fixed>" \
  --label "agent-reported" \
  --body "<structured body>"

PR body structure:

## Problem
<link to issue if filed, or describe the bug>

## Root Cause
<what was wrong and why>

## Fix
<what was changed and why this approach>

## Testing
<what tests were run, what was verified>

## Context
- Discovered during: <brief user task description>
- Thread: <thread_id>

Codebase Guide — Where to Look

Use this to identify the right module when filing issues or proposing fixes.

DirectoryWhat lives hereExample issues
skills/Skill SKILL.md instructions and assetsWrong examples in skills/dcf-model/SKILL.md, bug in a provided script snippet, outdated API usage, missing steps in a workflow, new best practice to add
mcp_servers/MCP server implementations (yfinance, fundamentals, macro, price_data)yfinance_mcp_server.py returns malformed data, a fundamentals endpoint is missing a field, macro data has wrong units
src/tools/External tool implementations (web fetch, crawl, search, SEC, market data)fetch.py times out on certain URLs, SEC filing parser fails on 10-K amendments, search returns stale results
src/ptc_agent/agent/tools/Core sandbox tools (ExecuteCode, Bash, file ops, grep, glob, think, todo)code_execution.py mishandles large stdout, bash.py doesn't escape special chars, file_ops.py fails on binary files
src/ptc_agent/agent/middleware/Middleware stack (skills, subagents, plan mode, compaction, memory, caching)Skill loading fails silently, subagent doesn't inherit context, compaction truncates important content
src/ptc_agent/agent/prompts/System prompt templates (Jinja2) and configRedundant or wrongful instructions in system.md.j2, useful tips and experience worth persisting into prompts

Label Convention

  • Always use agent-reported label
  • Add bug for broken behavior, enhancement for capability gaps
  • Add scope labels: skills, tools, mcp, prompt, sandbox

Safety Rules

  • NEVER push directly to main — always bot/fix/ or bot/feat/ branches
  • main branch contains the latest code. Always branch from main, target PRs to main
  • ALWAYS run linting and tests before creating a PR
  • Keep PRs small — one fix per PR, max 1-3 files
  • Clone to .self-improve/langalpha (inside workspace, persists across restarts)
  • NEVER commit tokens, secrets, API keys, or user data
  • NEVER include confidential or private information in issues or PRs — no user data, no internal business context, no API responses containing private data, no conversation content. Describe the technical problem only.
  • After filing/PR, immediately return to the user's original task

Pre-Submit Checklist

Go through EVERY item before running gh issue create or gh pr create:

  • User consent obtained — user explicitly approved filing this issue/PR
  • No secrets or tokens — title, body, and diff contain zero credentials, API keys, or env values
  • No private data — no user names, portfolio holdings, conversation content, or internal business context
  • No raw API responses — sanitize or omit any data returned from MCP tools or external APIs
  • Technical description only — the issue/PR describes the bug or fix, not what the user was working on
  • Correct repo — targeting ginlix-ai/LangAlpha
  • Correct branch (PRs only) — branched from main, PR base is main
  • Minimal diff (PRs only) — only the files needed for the fix, no unrelated changes

Frequently asked questions

What does the Self Improve AI skill do?

Report issues and propose fixes to improve your own capabilities when you encounter errors or limitations

Why use Self Improve on TypingMind?

Because you install it once and use it with any model. Self Improve 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 Self Improve in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_service/skills/self-improve. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Self Improve?

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 Self Improve?

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

Is the Self Improve AI skill free?

Yes. It is published on GitHub by ginlix-ai under the Apache-2.0 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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