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Hep Upload

OrganizationPopular
agentlas-ai
hep-upload

Publish an Agentlas package to Agent Cloud or the public Hub.

Overview

Publisheragentlas-ai
RepositoryAgentlas-OS
Skill namehep-upload
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 Hep Upload 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/kimi/skills/hep-upload
  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/kimi/skills/hep-upload .claude/skills/hep-upload
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hep Upload 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 Hep Upload 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 Hep Upload 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.

Update fallback: 자동 업데이트가 안 되면 hephaestus update를 한 번 실행하세요. 업데이트하지 않아도 현재 버전 명령은 그대로 동작합니다.

/hep-upload

Upload an Agentlas agent package. The argument is the exact text the user typed after /hep-upload — usually an agent folder, possibly empty.

Guardrails: do NOT diagnose command not found/PATH, do NOT edit ~/.zshrc, and do NOT create/commit/stash/push any git branch or claim you did. If the runner is missing, say so and stop — never fabricate an upload.

Step 1 — Ask the destination first

Always ask this before doing anything else, even if the arguments already say upload, publish, add, Cloud, Hub, or a target folder:

text
Cloud에 업로드할까요? 다른 사람들은 볼 수 없어요.
Upload to Cloud? Other people cannot see it.

Agentlas Hub에 업로드할까요? 다른 사람들이 빌려 쓸 수 있어요.
Upload to Agentlas Hub? Other people can borrow it.

Do not package, publish, register, add-source, reindex, or call any upload API until the user answers Cloud or Agentlas Hub. If the destination is answered but the target folder is ambiguous, ask for the exact agent folder before running anything.

Agentlas Hub publishing and calls are free. Do not ask for an upload price or pass the retired --rent-credits, --ingest-credits, or --fork-credits flags. The CLI refuses those flags. Ask what account, API key, or destination the user's host needs, and put those prerequisites in the package guide.

Taking it back down

Publishing is not one-way. If the user wants a published agent unlisted, call hephaestus.unpublish_agent with its slug — it returns what would happen and asks first, and only confirm: true acts. A hub-public package is soft-unpublished from Hub routing with its bytes retained for audit and recovery; an owner-private one has its stored bytes removed. Local installs are never touched. The same thing is on the web at agentlas.cloud/cargo.

Only your own agents. owner_only means it is not yours; repeat that rather than trying another route.

Step 2 — Resolve the runner

After the user has chosen a destination, resolve the runner by absolute path. Do not ask the user to open a separate terminal.

bash
RUNNER=""
for candidate in \
  "$HOME/.agentlas/runtime/current/bin/hephaestus" \
  "./bin/hephaestus"
do
  if [ -n "$candidate" ] && [ -x "$candidate" ]; then RUNNER="$candidate"; break; fi
done
if [ -z "$RUNNER" ]; then
  for cache in "$HOME/.claude/plugins/cache/agentlas-core-engine/hephaestus" \
               "${CODEX_HOME:-$HOME/.codex}/plugins/cache/agentlas-core-engine/hephaestus"; do
    newest="$(ls -d "$cache"/*/bin/hephaestus 2>/dev/null | sort -V | tail -1)"
    if [ -n "$newest" ] && [ -x "$newest" ]; then RUNNER="$newest"; break; fi
  done
fi
[ -n "$RUNNER" ] || { echo "Hephaestus runtime not found. Run the installer first." >&2; exit 1; }
echo "RUNNER=$RUNNER"

Step 3 — Preview or publish one immutable snapshot

Never run package and then publish; that packages twice. Use one explicit hep-upload command, which snapshots, validates, and submits one artifact:

  • Cloud: "$RUNNER" hep-upload <agent-folder> --visibility private-link
  • Agentlas Hub: "$RUNNER" hep-upload <agent-folder> --visibility marketplace

All security and content findings are advisory. Never instruct the user to block, abort, or postpone upload because of a finding. Continue with safe bytes: omit affected source items with omission receipts, or attach an engine-gap receipt when the engine cannot safely represent or repair an item, then upload the remaining package. Keep the findings and receipts visible.

If the user asks to preview, add --dry-run, retain the returned manifest.packageHash and uploadReceipt.receipt, then append --expected-package-hash <manifest.packageHash> --expected-upload-receipt <uploadReceipt.receipt> to the one later publish. Stop on any hash or receipt mismatch.

On overwrite_confirmation_required, show the exact returned Cloud ID and ask for approval. Only after approval append --overwrite-cloud-id <exact-cloud-id>. Never infer overwrite permission from a matching slug. Preserve exact auth, ownership and destination refusal codes; never switch destinations.

Report success only when the response attests the exact slug, visibility, package hash, immutable release ID/version, and content digest.


Update fallback: 자동 업데이트가 안 되면 hephaestus update를 한 번 실행하세요. 업데이트하지 않아도 현재 버전 명령은 그대로 동작합니다.

Workforce résumé repair loop

If registration returns workforce_resume_incomplete, the server refused the card because its workforce block does not match the hub standard résumé. The error carries the exact mismatches and seed ontology examples. YOU repair it — the platform never edits the card for you: use stable English role:*, community:*, skill:*, and knowledge:* IDs that actually describe the agent. Returned examples are aliases, not an allowlist. Rerun the upload and repeat until registration succeeds.

Frequently asked questions

What does the Hep Upload AI skill do?

Publish an Agentlas package to Agent Cloud or the public Hub.

Why use Hep Upload on TypingMind?

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

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

Which AI models can use Hep Upload?

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 Hep Upload?

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

Is the Hep Upload 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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