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Hephaestus Cloud

OrganizationPopular
agentlas-ai
hephaestus-cloud

Use when the user types /hep-cloud or /agentlas-cloud, or asks to staff from THEIR OWN Agentlas cloud packages only. Cloud is one exact source scope; Network means Local + owner Cloud + public Hub.

Overview

Publisheragentlas-ai
RepositoryAgentlas-OS
Skill namehephaestus-cloud
Stars
1.6K
Forks
111
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 agentlas-ai on GitHub. Read the source before you install it.

Installation

Install the Hephaestus Cloud 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/agentlas-ai/Agentlas-OS/tree/main/.agents/skills/hephaestus-cloud
  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/agentlas-ai/Agentlas-OS.git /tmp/Agentlas-OS
mkdir -p .claude/skills
cp -r /tmp/Agentlas-OS/.agents/skills/hephaestus-cloud .claude/skills/hephaestus-cloud
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hephaestus Cloud 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 Hephaestus Cloud 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 Hephaestus Cloud 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.

Hephaestus Cloud Routing (my own cloud / 보관함)

Route the request through the signed-in user's OWN Agentlas cloud packages only. The active host LLM remains the staffing decision-maker; Cloud supplies a content menu and exact BYOM releases.

0. Scope rule

/hep-cloud is owner-scoped: it queries ONLY the authenticated owner's own cloud packages (보관함) through Core's typed sourceScope: "cloud". It does not search the public marketplace and does not search local private/plugin cards.

  • The user's own Cloud packages are restorable/owned by them. Entitlement, lease, and charged credits are server-authoritative; do not hard-code a price.
  • For the public marketplace only, use /hep-hub (sourceScope: "hub").
  • For the combined Local + own Cloud + public Hub menu, use /hep-network (sourceScope: "network").

Each unpinned Cloud discovery goes to the owner-scoped source for its current menu; a successful client cache entry must not hide a newly published, replaced, or removed package. Once the host validates and prepares a choice, the exact Cloud release remains pinned for that execution.

1. Resolve the runner

Run this resolution in a shell and use the first hit:

bash
RUNNER=""
for c in \
  "$HOME/.agentlas/runtime/current/bin/hephaestus" \
  ./bin/hephaestus
do [ -x "$c" ] && RUNNER="$c" && break; done
if [ -z "$RUNNER" ]; then
  for cache in \
    "$HOME/.claude/plugins/cache/agentlas-core-engine/hephaestus" \
    "$HOME/.codex/plugins/cache/agentlas-core-engine/hephaestus"; do
    newest="$(ls -d "$cache"/*/bin/hephaestus 2>/dev/null | sort -V | tail -1)"
    [ -n "$newest" ] && [ -x "$newest" ] && RUNNER="$newest" && break
  done
fi

If no runner exists, tell the user to run the one-touch installer: curl -fsSL https://raw.githubusercontent.com/agentlas-ai/Agentlas-OS/main/scripts/install-all-runtimes.sh | bash

If shell execution is unavailable but the local hephaestus-network MCP is available, use the typed Workforce sequence in section 3. If that server cannot advertise owner-Cloud search plus exact bundle fetch, report source_not_supported; never fall back to the legacy cargo search path.

1.5 Core project first-contact contract

The cloud ... --project . call below is a trusted plugin contact. Agentlas Core must synchronously create or repair the same private project soul memory, code map, ontology runtime, CareerGraph, and full .agentlas/ ignore block used by every other host. If bootstrap is blocked, stop rather than querying Cloud without the project architecture. The adapter never owns a second seed format.

2. Agentlas sign-in (required)

The owner cloud is sign-in-gated. Before routing, ensure Agentlas is signed in:

bash
if [ "${HEPHAESTUS_AUTH_AUTOPOPUP:-1}" != "0" ]; then
  "$RUNNER" auth ensure >/dev/null 2>&1 || true
fi

This opens the user's default browser only when there is no valid local sign-in yet, and reuses a saved sign-in silently. For CI/headless checks only, set HEPHAESTUS_AUTH_AUTOPOPUP=0 and skip this step.

3. Staff from owner Cloud only

In an MCP-capable host, author the complete redacted WorkOrder, then call the actual local Core tools in this order:

text
workforce.search_candidates(sourceScope="cloud")
workforce.validate_selection(workOrder=..., selection=...)
workforce.prepare_execution(workOrder=..., selection=..., federatedSelection=..., projectDir=..., goalId=activeGoalId?)
workforce.validate_execution_receipt(receipt=..., executionPlan=..., toolInventory=...)

The host LLM authors the final Selection. If the deployed owner-Cloud Workforce source contract is absent, report source_not_supported; do not silently query public Hub or legacy cargo search. A shell without an active host LLM can only report that orchestration is required.

The default search response is a projected menu. Preserve its Cloud source receipt and selectionSessionId, but do not echo it as a complete federationResult; Core resolves the full pinned result by session. Receipt validation is local and read-only and cannot create execution evidence.

4. Act on the typed result (scope: "cloud")

Preserve the Cloud source receipt, source selection session, candidate-set digest, release id, package hash, and content digest. Validate and prepare in local Core; never send the federated wrapper back to remote validation.

5. Hard rules

  • Never report public marketplace agents or local private/plugin cards as if they were the user's own cloud packages.
  • Deterministic Core validates governance and immutable pins but never chooses the roster. The active host LLM chooses from content evidence.
  • For actual tool execution, follow the host runtime's safety and permission model. Report the exact source receipt plus selectionReceiptId, preparationReceiptId, and validated execution receipt status when present.

Frequently asked questions

What does the Hephaestus Cloud AI skill do?

Use when the user types /hep-cloud or /agentlas-cloud, or asks to staff from THEIR OWN Agentlas cloud packages only. Cloud is one exact source scope; Network means Local + owner Cloud + public Hub.

Why use Hephaestus Cloud on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agentlas-ai/Agentlas-OS/tree/main/.agents/skills/hephaestus-cloud. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hephaestus Cloud?

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 Hephaestus Cloud?

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

Is the Hephaestus Cloud AI skill free?

Yes. It is published on GitHub by agentlas-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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