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Hindsight Local

OrganizationPopular
vectorize-io
hindsight-local

Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)

Overview

Publishervectorize-io
Repositoryhindsight
Skill namehindsight-local
Stars
44K
Forks
5.8K
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 vectorize-io on GitHub. Read the source before you install it.

Installation

Install the Hindsight Local 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/vectorize-io/hindsight/tree/main/skills/hindsight-local
  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/vectorize-io/hindsight.git /tmp/hindsight
mkdir -p .claude/skills
cp -r /tmp/hindsight/skills/hindsight-local .claude/skills/hindsight-local
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hindsight Local 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 Hindsight Local 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 Hindsight Local 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.

Hindsight Memory Skill (Local)

You have persistent memory via the hindsight-embed CLI. Proactively store learnings and recall context to provide better assistance.

Setup Check (First-Time Only)

Before using memory commands, verify Hindsight is configured:

bash
uvx hindsight-embed daemon status

If this fails or shows "not configured", run the interactive setup:

bash
uvx hindsight-embed configure

This will prompt for an LLM provider and API key. After setup, the commands below will work.

How Hindsight Works

When you call retain, Hindsight does not store the string as-is. The server runs an internal pipeline that:

  1. Extracts structured facts from the content using an LLM
  2. Identifies entities (people, tools, concepts) and links related facts
  3. Builds temporal and causal relationships between facts
  4. Generates embeddings for semantic search

This means you should pass rich, full-context content — the server is better at extracting what matters than a pre-summarized string. Your job is to decide when to store, not what to extract.

Commands

Store a memory

Use memory retain to store what you learn. Pass the full context — raw observations, session notes, conversation excerpts, or detailed descriptions:

bash
uvx hindsight-embed memory retain default "User is working on a TypeScript project. They enabled strict mode and prefer explicit type annotations over inference."
uvx hindsight-embed memory retain default "Ran the test suite with NODE_ENV=test. Tests pass. Without NODE_ENV=test, the suite fails with a missing config error." --context procedures
uvx hindsight-embed memory retain default "Build failed on Node 18 with error 'ERR_UNSUPPORTED_ESM_URL_SCHEME'. Switched to Node 20 and build succeeded." --context learnings

You can also pass a raw conversation transcript with timestamps:

bash
uvx hindsight-embed memory retain default "[2026-03-16T10:12:03] User: The auth tests keep failing on CI but pass locally. Any idea?
[2026-03-16T10:12:45] Assistant: Let me check the CI logs. Looks like the tests are running without the TEST_DATABASE_URL env var set — they fall back to the production DB URL and hit a connection timeout.
[2026-03-16T10:13:20] User: Ah right, I never added that to the CI secrets. Adding it now.
[2026-03-16T10:15:02] User: That fixed it. All green now." --context learnings

Recall memories

Use memory recall BEFORE starting tasks to get relevant context:

bash
uvx hindsight-embed memory recall default "user preferences for this project"
uvx hindsight-embed memory recall default "what issues have we encountered before"

Reflect on memories

Use memory reflect to synthesize context:

bash
uvx hindsight-embed memory reflect default "How should I approach this task based on past experience?"

IMPORTANT: When to Store Memories

Always store after you learn something valuable:

User Preferences

  • Coding style (indentation, naming conventions, language preferences)
  • Tool preferences (editors, linters, formatters)
  • Communication preferences
  • Project conventions

Procedure Outcomes

  • Steps that successfully completed a task
  • Commands that worked (or failed) and why
  • Workarounds discovered
  • Configuration that resolved issues

Learnings from Tasks

  • Bugs encountered and their solutions
  • Performance optimizations that worked
  • Architecture decisions and rationale
  • Dependencies or version requirements

IMPORTANT: When to Recall Memories

Always recall before:

  • Starting any non-trivial task
  • Making decisions about implementation
  • Suggesting tools, libraries, or approaches
  • Writing code in a new area of the project

Best Practices

  1. Store immediately: When you discover something, store it right away
  2. Pass rich context: Include full observations, not pre-summarized strings — the server extracts facts automatically
  3. Include outcomes: Store what happened AND why, including failures and workarounds
  4. Recall first: Always check for relevant context before starting work
  5. Use --context for metadata: The --context flag labels the type of memory (e.g., procedures, learnings, preferences), not a replacement for full content

Frequently asked questions

What does the Hindsight Local AI skill do?

Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)

Why use Hindsight Local on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vectorize-io/hindsight/tree/main/skills/hindsight-local. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hindsight Local?

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 Hindsight Local?

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

Is the Hindsight Local AI skill free?

Yes. It is published on GitHub by vectorize-io 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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