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Memory

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codeaholicguy
memory

AI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.

Overview

Publishercodeaholicguy
Repositoryai-devkit
Skill namememory
Stars
1.6K
Forks
252
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Memory 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/codeaholicguy/ai-devkit.git /tmp/ai-devkit
mkdir -p .claude/skills
cp -r /tmp/ai-devkit/skills/memory .claude/skills/memory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Memory 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 Memory 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 Memory 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.

AI DevKit Memory CLI

Use npx ai-devkit@latest memory ... as the durable knowledge layer.

Workflow

  1. For implementation, debugging, review, planning, or documentation tasks, search before deep work unless the task is trivial:

    bash
    npx ai-devkit@latest memory search --query "<task, subsystem, error, or convention>" --limit 5

    For broad or risky tasks, search multiple angles: subsystem, error text, framework, command, and task intent.

  2. Use results as context:

    • Trust repo files, tests, fresh command output, and explicit user instructions over memory.
    • If memory conflicts with verified evidence, use the evidence and update the stale memory.
    • Mention memory only when it changes the plan or avoids asking the user again.
  3. Search before storing:

    bash
    npx ai-devkit@latest memory search --query "<knowledge to store>" --table
  4. Store or update only after the quality gate passes.

Quality Gate

Before storing, all must be true:

  • Future sessions are likely to reuse it.
  • It is verified by code, docs, tests, command output, or explicit user instruction.
  • It is not merely a restatement of obvious nearby files unless it prevents repeated agent mistakes.
  • It is scoped narrowly enough.
  • Existing memory does not already cover it.
  • It contains no secrets, credentials, private customer data, personal data, raw logs, or temporary paths.

Store:

  • Project conventions, user preferences, durable decisions.
  • Reusable fixes, testing patterns, commands, setup gotchas.
  • Non-obvious constraints, architecture rules, failure patterns.

Do not store:

  • Task progress, transcripts, speculation, generic programming facts.
  • Raw errors without diagnosis.
  • Anything the user did not intend to persist.

Commands

Search

bash
npx ai-devkit@latest memory search \
  --query "<query>" \
  --tags "<tags>" \
  --scope "<scope>" \
  --limit 5

Use --table to get IDs for updates:

bash
npx ai-devkit@latest memory search --query "<query>" --table

Options: --query/-q required; --tags; --scope/-s; --limit/-l from 1-20; --table.

Store

bash
npx ai-devkit@latest memory store \
  --title "<actionable title, 10-100 chars>" \
  --content "<context, guidance, evidence, exceptions>" \
  --tags "<lowercase,tags>" \
  --scope "<global|project:name|repo:org/repo>"

Use this content shape when helpful:

text
Context: Where this applies.
Guidance: What to do.
Evidence: File, command, test, or user instruction.
Exceptions: When not to apply it.

Update

Find the ID with search --table, then update only changed fields:

bash
npx ai-devkit@latest memory update \
  --id "<memory-id>" \
  --title "<updated title>" \
  --content "<updated content>" \
  --tags "<replacement,tags>" \
  --scope "<updated scope>"

--tags replaces all existing tags.

Scoping

Use the narrowest useful scope:

  • repo:<org/repo> for one repository.
  • project:<name> for one app, product, or workspace.
  • global only for knowledge that applies across unrelated projects.

If unsure, use a narrower scope.

Troubleshooting

  • CLI missing: run npx ai-devkit@latest --version.
  • Duplicate title: search, then update the existing item if it is the same knowledge.
  • Empty results: broaden terms, remove filters, or search symptoms and subsystem names separately.
  • Validation error: check title/content lengths, query length, and --limit range.
  • DB path: default is ~/.ai-devkit/memory.db; project config can override it automatically.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Memory AI skill do?

AI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.

Why use Memory on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codeaholicguy/ai-devkit/tree/main/skills/memory. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Memory?

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 Memory?

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

Is the Memory AI skill free?

Yes. It is published on GitHub by codeaholicguy 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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