Hyperloom Kb logo

Hyperloom Kb

Organization
AMD-AGI
hyperloom-kb

Operates an Experience KB service with the hyperloom-kb CLI. Checks its health, labels its state, restores a label to roll back, excludes or includes an Experience with a reason, and lists or exports what was written to it. Use when asked to label, roll back, restore, exclude, include, list, or export Experiences, or to embed these commands in another tool.

Overview

PublisherAMD-AGI
RepositoryHyperloom
Skill namehyperloom-kb
Stars
250
Forks
74
Bundled files
Instructions only
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 AMD-AGI on GitHub. Read the source before you install it.

Installation

Install the Hyperloom Kb 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/AMD-AGI/Hyperloom/tree/main/src/hyperloom_kb/skills/hyperloom-kb
  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/AMD-AGI/Hyperloom.git /tmp/Hyperloom
mkdir -p .claude/skills
cp -r /tmp/Hyperloom/src/hyperloom_kb/skills/hyperloom-kb .claude/skills/hyperloom-kb
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hyperloom Kb 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 Hyperloom Kb 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 Hyperloom Kb 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.

Operate an Experience KB

hyperloom-kb talks to one Experience KB service: the one HYPERLOOM_KB_URL names, authenticated with HYPERLOOM_KB_TOKEN. Run it as hyperloom-kb <command>, or as python3 -m hyperloom_kb.cli <command> where the package is importable but the command is not on PATH.

Load both variables from wherever the user keeps them without printing them. Never echo the token, and do not ask the user to paste it into chat.

Every command prints its result as JSON and exits:

  • 0 when it worked;
  • 1 when the service refused the request (the message on stderr names the HTTP status);
  • 2 when the URL or the token is not configured.

When a tool embeds these commands (see the last section), run them through that tool instead: it supplies its own schema.

The state reads see

Each schema on a service has one current state: the Experiences stored there, minus the excluded ones. Reads see exactly that state. Nothing is ever deleted.

bash
hyperloom-kb health                  # kb_id, name, and what reads see per schema
hyperloom-kb labels [--schema REF]   # labels newest first, current_label_id, modified

modified: true means the state changed since its current label, or that a non-empty state has no label yet. A command that names no schema acts on the service's default schema, the schema_ref in health.

Health and metrics

hyperloom-kb health reports the KB's identity and what its reads see per schema. Three endpoints answer without a token, for an orchestrator, a metrics scraper, or a quick look:

bash
curl -s "$HYPERLOOM_KB_URL/readyz"    # ready, and which check failed when not
curl -s "$HYPERLOOM_KB_URL/metrics"   # Prometheus metrics: requests, latency, writes, storage

A failure hyperloom-kb reports names its request id; the service logs one JSON line per request with that request_id, so search its log for it.

Label and restore

bash
hyperloom-kb label [--schema REF] [--name "before tuning"]
hyperloom-kb restore LABEL_ID
  • A label is identified by its label_id. Its name is only for people and need not be unique, so always restore by label_id.
  • A restore makes the label's state current: the Experiences and the exclusions it held. Experiences written after the label leave the state, and later writes add to the restored one.
  • When the current state is not what its label saved, the restore first labels it (reason before_restore) and answers that label as saved. Report its label_id: restoring it brings the state back.

Exclude and include

bash
hyperloom-kb exclude EXPERIENCE_ID --reason "measured on a noisy node"
hyperloom-kb include EXPERIENCE_ID
hyperloom-kb exclusions [--schema REF]
  • An exclusion hides an Experience from reads. Ask for the reason when the user gave none; it stays in the history.
  • include lifts the exclusion, and also puts back an Experience a restore set outside the state, so one no label holds any more, after its label was deleted, can still be brought back. It answers not_excluded when the Experience was neither excluded nor outside the state.
  • exclusions lists the current exclusions and every exclude and include.

List and export

bash
hyperloom-kb list   [--schema REF] [--include-excluded] [--after N] [--limit N]
hyperloom-kb export [--schema REF] [--include-excluded] [--after N] [--limit N]

Both name the Experiences written to this service, and of those only what reads see unless --include-excluded asks for the rest. Without --schema they cover every schema. Each call returns one page: repeat with --after <next_cursor> while has_more is true. list returns summaries; export returns complete records and, with --schema, that schema's declaration.

Embed the commands in another tool

A tool with its own CLI gets every command above, with its own default schema:

python
from hyperloom_kb import RemoteClient
from hyperloom_kb.cli import add_commands, run_command

commands = parser.add_subparsers(dest="command", required=True)
commands.add_parser("list", help="The tool's own list.")  # registered first, so it replaces the generic one
add_commands(commands, schema_ref=TOOL_SCHEMA_REF)
args = parser.parse_args()
if hasattr(args, "run"):  # one of the commands add_commands registered
    raise SystemExit(run_command(RemoteClient(tool_config), args))  # tool_config: the RemoteConfig of its service

add_commands registers every command whose name the tool has not registered yet. Each one that names no schema acts on schema_ref, list and export included. run_command prints the same JSON and returns the same exit status as hyperloom-kb.

Frequently asked questions

What does the Hyperloom Kb AI skill do?

Operates an Experience KB service with the hyperloom-kb CLI. Checks its health, labels its state, restores a label to roll back, excludes or includes an Experience with a reason, and lists or exports what was written to it. Use when asked to label, roll back, restore, exclude, include, list, or export Experiences, or to embed these commands in another tool.

Why use Hyperloom Kb on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AMD-AGI/Hyperloom/tree/main/src/hyperloom_kb/skills/hyperloom-kb. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hyperloom Kb?

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 Hyperloom Kb?

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

Is the Hyperloom Kb AI skill free?

It is published on GitHub by AMD-AGI. Check the repository for licensing terms. 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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