Jevopus Getting Started logo

Jevopus Getting Started

Community
Bodila51
jevopus-getting-started

Use on a new owner's first conversation with the Jevopus bot, when the user asks what Jevopus can do or how to set it up, or when they ask how to work with it: silently read their whole Grok Bot context, map their hardest real tasks to Grok, Claude, ChatGPT Codex or Jev, walk through setup step by step with a test after each step, then explain fully how to use it.

Overview

PublisherBodila51
Repositorygrok-bot-jev
Skill namejevopus-getting-started
Stars
113
Forks
16
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 Bodila51 on GitHub. Read the source before you install it.

Installation

Install the Jevopus Getting Started 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/Bodila51/grok-bot-jev/tree/main/jevopus/skills/jevopus-getting-started
  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/Bodila51/grok-bot-jev.git /tmp/grok-bot-jev
mkdir -p .claude/skills
cp -r /tmp/grok-bot-jev/jevopus/skills/jevopus-getting-started .claude/skills/jevopus-getting-started
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jevopus Getting Started 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 Jevopus Getting Started 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 Jevopus Getting Started 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.

Jevopus: first conversation and guided setup

Reply in the user's language. Keep each message short; one step at a time. Never invent facts about the owner: every suggestion must point to a real signal you found.

1. Read the owner's context first (silently, before the first message)

Collect only what is already available to you; don't ask the owner questions yet.

  • Teammates: every other bot in your context. Note each bot's name, description and what kind of work it does (code, writing, research, outreach, finance, support...).
  • Their skills: the skill catalog (names and descriptions) shows what workflows the owner already runs.
  • Routines: your own and, where visible, teammates' scheduled or event jobs. Recurring = good candidate for a seat.
  • Connectors: GetMcpServerStatus (GitHub, Gmail, X, Slack, Google Drive/Sheets, Notion, Linear, finance...). Connected service = real data the seats can work on.
  • Memory: RecallMemory scope "user" (and "all") for role, company, projects, language, audience, recurring pains, deadlines.
  • Computer: /workspace folders, repos or data files other bots left there (names only; don't open private files without reason). Check /workspace/jevopus/jevopus.py; if it exists run python3 /workspace/jevopus/jevopus.py doctor.
  • Do not read other bots' full transcripts unless the owner agrees.

2. Build the owner's task map

From the signals, list 5 to 7 concrete, heavy tasks this owner plausibly has (long, multi-step, or quality-critical; not quick chat). For each decide who does it:

  • Grok itself (no seat): quick answers, short edits, lookups, anything done in one or two steps. Say so honestly: most daily work doesn't need a seat.
  • Claude Code (Opus/Sonnet/Haiku): long careful writing, deep analysis and reasoning, reviewing and refactoring existing code, long documents, strategy.
  • ChatGPT Codex (GPT): building code, scripts and apps from scratch, data processing, spreadsheets and file conversions, automation.
  • Jev picks: when both fit, when cost matters, or for recurring jobs where past results should decide. Jev chooses the model and effort per job and learns from the owner's good/wrong feedback. Claude and ChatGPT are equal options; the split above is a starting heuristic, not a rule. Mention "best of two" for quality-critical jobs (both models run, the better result wins).

3. First message

  1. One short paragraph: Jevopus runs big jobs on ChatGPT Codex and Claude Code seats (the owner's existing subscriptions, not API billing) on its own computer, 24/7. Grok handles the easy work; only the tasks where a stronger model clearly helps go to a seat, and Jev picks which one. It checks results and stops before sending, paying or deleting.
  2. The task map as a short list: task, who does it (Grok / Claude / ChatGPT / Jev), why in a few words, and the signal it came from ("your X API bot builds apps", "GitHub is connected", "memory says you write weekly reports").
  3. If you found almost nothing, say so and offer the generic recipes instead: research brief, landing page, code review, data cleanup, X post drafts, short video, lead finder with pitch drafts, media kit, competitor analysis, presentation.
  4. End with: setup takes about 5 minutes, then I can start with task #1. Start now?

4. Setup, one step per message, test after each

  1. Install: run jevopus-install (background). Report doctor's result in plain words.
  2. Models: ask which they have (widget, multi-select): ChatGPT subscription, OpenAI API key, Claude (Claude Code). Set up each chosen seat per jevopus-operate:
    • ChatGPT: setup-seat codex-sub, send the URL and one-time code; they confirm in their own browser.
    • OpenAI API key: warn first that API usage is billed separately from ChatGPT and needs a positive balance; secret-request OPENAI_API_KEY, then setup-seat codex-api.
    • Claude Code: install the CLI if needed, then setup-seat claude-strong and walk them through the Claude login. The seat offers Opus, Sonnet and Haiku; Jev picks among them per job. Each seat is enabled only after its live test passes; tell them what passed. If they only have one of the two, adjust the task map: tasks marked for the missing model go to the connected one or stay with Grok, and say so.
  3. Jev: secret-request TYPESAFE_API_KEY (key from their TypeSafe account). Test with doctor's "live Jev call" line. Without it Jevopus still works on keyword rules.
  4. If a saved key is not visible to doctor: keys reach the computer only after Update Grok Bot's Computer. Send the link, wait, re-run doctor. Tools in ~/.local usually survive; re-run jevopus-install if doctor says a CLI is missing.

5. Explain how to work with you (also whenever they ask "how do I work with you?")

Run python3 /workspace/jevopus/jevopus.py guide and explain all of it in the owner's language. Don't paste the English text: translate it naturally and keep every point: plain-word tasks, naming a model and what happens if it isn't connected, best of two, the recipe list, limits, reports with the exact prompt and log, good/wrong feedback teaching model choice, other bots via JEVOPUS JOB, their yes for anything irreversible, weekly updates only with their yes, Jev shadow/active mode. Include the "Now:" line about which seats and models are connected. Remind them that other bots from the task map can hand jobs over with a JEVOPUS JOB message.

6. First real job and optional tests (only if the owner agrees)

Offer to run task #1 from the map as the first real job. Optional checks, each using a little seat allowance except the first: (a) jevopus.py limits; (b) a research brief with live web search on a short topic, then check it cites real, current URLs; (c) with two models connected, a best-of-two test on a small task (--best-of-two), then report to show both results and the winner. Run only what they accept and report tokens and results after each.

7. Wrap up

Offer a weekly routine that checks for Jevopus updates (see jevopus-operate) and, if it fits, turn a recurring task from the map into a routine that hands the job to a seat. Create routines only if they agree. Never ask for a pasted key, never print secrets, never run sends, payments or deletions without their explicit yes.

Frequently asked questions

What does the Jevopus Getting Started AI skill do?

Use on a new owner's first conversation with the Jevopus bot, when the user asks what Jevopus can do or how to set it up, or when they ask how to work with it: silently read their whole Grok Bot context, map their hardest real tasks to Grok, Claude, ChatGPT Codex or Jev, walk through setup step by step with a test after each step, then explain fully how to use it.

Why use Jevopus Getting Started on TypingMind?

Because you install it once and use it with any model. Jevopus Getting Started 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 Jevopus Getting Started in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Bodila51/grok-bot-jev/tree/main/jevopus/skills/jevopus-getting-started. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Jevopus Getting Started?

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 Jevopus Getting Started?

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

Is the Jevopus Getting Started AI skill free?

Yes. It is published on GitHub by Bodila51 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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