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Ultragoal

CommunityPopular
Yeachan-Heo
ultragoal

Durable multi-goal workflow that persists plan/ledger artifacts under .omc/ultragoal and prints Claude /goal handoff text for the active session

Overview

PublisherYeachan-Heo
Repositoryoh-my-claudecode
Skill nameultragoal
Stars
39.2K
Forks
3.5K
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 Yeachan-Heo on GitHub. Read the source before you install it.

Installation

Install the Ultragoal 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.
  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/Yeachan-Heo/oh-my-claudecode.git /tmp/oh-my-claudecode
mkdir -p .claude/skills
cp -r /tmp/oh-my-claudecode/skills/ultragoal .claude/skills/ultragoal
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ultragoal 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 Ultragoal 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 Ultragoal 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.

<Use_When>

  • The user wants a durable, repo-native way to track an ultragoal across multiple Claude sessions or worktrees
  • The work is large enough to warrant multiple ordered "stories" with attempt counts and per-story evidence
  • The user wants the final completion gated behind ai-slop-cleaner + verification + $code-review
  • The user wants the active Claude /goal directive coordinated with the ledger so that a session restart does not lose progress </Use_When>

<Do_Not_Use_When>

  • The task is a single small change — use direct delegation or ralph instead
  • The user wants the assistant to literally invoke /goal itself from the shell — that is not possible; omc ultragoal only writes artifacts and prints handoff text
  • The user wants a planning-only artifact with no execution loop — use plan instead </Do_Not_Use_When>

<Why_This_Exists> Claude Code /goal is a session-scoped Stop hook: it blocks the session from stopping until a condition holds, and auto-clears on success. That is a great single-session execution primitive, but it loses state across sessions and does not by itself enforce a final review gate. omc ultragoal adds a durable plan, ledger, and gating layer so a long multi-step initiative can survive session restarts, fresh worktrees, and review iterations while still leveraging Claude /goal to keep the active agent focused. </Why_This_Exists>

<How_To_Use>

  1. Create a plan from a brief:

    omc ultragoal create-goals --brief-file plan.md

    Or with explicit stories:

    omc ultragoal create-goals --brief "ship the migration" \
      --goal "Schema::Add new columns" \
      --goal "Backfill::Backfill rows in batches" \
      --goal "Cutover::Drop old columns and switch reads"

    The default mode is aggregate (one Claude /goal covers the run). Pass --claude-goal-mode per-story if you want each story to have its own /goal.

    Multi-repo workspaces / parallel sessions: when several Claude sessions in the same workspace need to run /ultragoal concurrently, pass either --plan-id <stable-id> or --auto-plan-id so the plan is written to .omc/ultragoal/plans/{planId}/ instead of the shared single-plan path. Without that flag, two sessions creating goals would clobber each other. --auto-plan-id derives {epochMs}-{slug} from the brief title. Then thread the same --plan-id <id> through every subsequent subcommand in that session. Use omc ultragoal list-plans to enumerate available planIds when needed.

  2. Start (or resume) the next story:

    omc ultragoal complete-goals [<goal-id>]

    With no goal id, this preserves the default behavior of resuming the active story or starting the first pending story. With a goal id, OMC targets exactly that named eligible story (a pending story may be started out of order); it never falls through to another story. An active different story, unknown id, completed or review-blocked story, or failed story without --retry-failed is rejected without state mutation. An in-progress named story is resumed without changing its attempt. This prints a model-facing handoff. The active Claude agent must read it and:

    • Set the native Claude /goal for this session — in standalone Claude Code neither the shell nor the agent can do it, so ask the user to type /goal <aggregate objective> and wait. --claude-goal-json (below) reconciles the ledger only and does not satisfy the PreToolUse /goal guard, which blocks tool calls until it observes an active /goal.
    • Work the story.
    • When the story is complete (and for the final story, after the full quality gate), share back a snapshot of the active /goal state and call checkpoint.
  3. Checkpoint a story:

    omc ultragoal checkpoint --goal-id G001-... --status complete \
      --evidence "tests/files/PR evidence" \
      --claude-goal-json '{"goal":{"objective":"...","status":"active"}}'

    For the final story, also pass --quality-gate-json containing aiSlopCleaner, verification, and codeReview evidence (all clean).

  4. If the final review is not clean, do NOT mark complete. Record blockers:

    omc ultragoal record-review-blockers --goal-id G00X-... \
      --title "Resolve final code-review blockers" \
      --objective "Fix the listed review findings and rerun final gates" \
      --evidence "<the review findings>" \
      --claude-goal-json '{"goal":{"objective":"...","status":"active"}}'

    This appends a new blocker story and keeps the Claude /goal active.

  5. Inspect state at any time:

    omc ultragoal status

</How_To_Use>

<Important_Limitations>

  • The shell cannot invoke or mutate Claude Code /goal state. omc ultragoal only persists durable artifacts and prints instructions that the active Claude agent reads and acts on in-session.
  • Snapshots passed via --claude-goal-json are model-supplied proof of the active /goal state; OMC validates them for textual consistency with the plan's expected objective and ledger event, but it cannot independently observe Claude /goal state. They do not satisfy the PreToolUse /goal guard, which requires an actual active /goal — a host-injected snapshot or the native /goal the user set in-session.
  • If the Claude /goal slash command is renamed or restructured, only the handoff wording needs to change; the reconciliation logic is name-agnostic. </Important_Limitations>

Parallel session caveats

  • Multi-repo workspace anchor: drop a .omc-workspace marker at the parent directory so multiple sessions across sub-repos share one .omc/. Resolution order: OMC_STATE_DIR > .omc-workspace > git > cwd. See docs/REFERENCE.md.
  • Session id source: OMC_SESSION_ID env var wins in CLI contexts; hook payload data.session_id wins in hook contexts.
  • Plan id (when applicable): Two runs in the same workspace will conflict on shared plan artifacts. Use distinct session IDs (the hook payload session_id is already isolated per Claude Code session), or pass --plan-id to keep parallel ultragoal runs on separate ledgers.
  • Parallel verdict: supported (each session writes its own session-scoped state)

Frequently asked questions

What does the Ultragoal AI skill do?

Durable multi-goal workflow that persists plan/ledger artifacts under .omc/ultragoal and prints Claude /goal handoff text for the active session

Why use Ultragoal on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/ultragoal. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ultragoal?

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 Ultragoal?

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

Is the Ultragoal AI skill free?

Yes. It is published on GitHub by Yeachan-Heo 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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