Ultragoal logo

Ultragoal

CommunityPopular
huytieu
ultragoal

Run a large, multi-session goal (e.g. shipping a whole side product) through the full V-model closed loop, one phase at a time, with cross-session state and a final north-star acceptance gate. Ultragoals never downgrade the lane: every phase runs CP-1→CP-6 with adversarial verification. Opt-in: invoke with /ultragoal or by calling something a long-running goal. Ordinary work does not run this.

Overview

Publisherhuytieu
RepositoryCOG-second-brain
Skill nameultragoal
Stars
1.2K
Forks
138
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 huytieu 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/huytieu/COG-second-brain.git /tmp/COG-second-brain
mkdir -p .claude/skills
cp -r /tmp/COG-second-brain/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.

Ultragoal — the closed loop for goals too big to ship in one run

An ultragoal is the term for a north-star that spans many sessions: fork the repos, combine the strong parts, ship one product. A /closed-loop run is one task through the loop. An ultragoal is a chain of phases, each of which is its own full closed-loop run, tracked so any cold session can resume.

Core rule (from dwarves-kit, adopted fully): the worker never grades its own homework, and wrongness compounds across sessions — so verify every phase, not just the end.

When to use

  • /ultragoal <name> — resume or advance an existing ultragoal
  • /ultragoal new "<north-star>" — charter a new one
  • /ultragoal status — report all ultragoals from the registry
  • Trigger phrases: "make this an ultragoal", "this is a long-running goal", "combine these into one product over time"

Do not use for single-run work (that is /closed-loop), and do not start one on a request that never asked for one. Rule of thumb: if it needs a phase decomposition and won't finish today, it is an ultragoal.

Files (one goal = one folder)

FileRole
04-projects/harness/ultragoals.mdRegistry: every ultragoal, status, current phase
04-projects/<goal>/spec.mdContract: north-star + AC-n acceptance criteria + phases P0…Pn + traceability matrix
04-projects/<goal>/STATUS.mdLiving ledger: phase state, current phase, open AC-n, next action (resume from here)
04-projects/<goal>/evidence/P<n>/Per-phase evidence bundle (ledger.md + CP-* files)

Code, if any, lives outside the vault (e.g. ~/code/<goal>/) — the spec/status/evidence stay in the vault.

Phase 0 — Charter (/ultragoal new)

  1. Interview the user for the north-star in one sentence (what "done" looks like).
  2. Write 04-projects/<goal>/spec.md from ../closed-loop/references/spec-template.md:
    • North-star statement
    • Falsifiable AC-n acceptance criteria (these define done for the whole goal)
    • Phase decomposition P0…Pn — each phase is a shippable increment mapped to a subset of AC-n
    • Traceability matrix (AC-n ↔ phase ↔ status)
  3. Create STATUS.md (see template below) and add a row to the registry.

Record: bash .claude/lib/checkpoint.sh record 04-projects/<goal>/evidence/P0 CP-1 PASS "N criteria, M phases"

The phase loop (every phase, no lane downgrade)

Each phase runs the full closed loop. Do not shortcut with tiny. Ultragoals are full lane by construction.

select next phase from STATUS.md
CP-2 PLAN     tasks for this phase ↔ AC-n   → evidence/P<n>/CP-2-plan.md
CP-3 BUILD    worker implements (traced to AC-n); returns paths only
CP-3v VERIFY  task-verifier (fresh context, read-only) → evidence rows per AC-n
        │       ├── FAIL:fixable → fix-agent (max 2) → re-verify
        │       └── FAIL:escalate → stop, escalate to the user
CP-4 INTEGRATE  integration-verifier → does this phase wire correctly with prior phases?
        │        (always run for ultragoals — cross-phase regression is the main risk)
CP-5 ACCEPT   observe the artifact (curl / screenshot / re-fetch), not the tool return
        │       EVIDENCE AC-n | CP-5 | PASS | <observation> | <artifact>
CP-6 SHIP     external mutation? → Review Gate: you approve. Internal? → auto.
update STATUS.md (phase → done, advance current phase, log open AC-n)
CP-7 RETRO    /retro 04-projects/<goal>/evidence/P<n>  → harvest + STATUS

Merge every verifier's EVIDENCE rows into evidence/P<n>/ledger.md.

The two acceptance gates

  1. Per-phase (CP-5): every AC-n this phase claims has a PASS row before the phase is marked done.
  2. North-star (final): before the ultragoal is declared complete, spawn a fresh-context verifier whose only job is to check the spec matrix — every AC-n across all phases has ≥1 PASS evidence row. Any AC-n without one is a gap, not a ship. This is the ultragoal-level analogue of CP-5.
North-star acceptance:
  read spec.md matrix (all AC-n)
  read every evidence/P*/ledger.md
  for each AC-n: assert ≥1 PASS row exists, artifact re-observed
  any miss → list open AC-n, STATUS stays "in progress", do NOT declare done

The HTML report (regenerate at every phase gate + final)

Every ultragoal carries a single self-contained HTML report that covers everything: north-star, live status, all phases, the full AC-n traceability table with pass/open/fail, evidence rows per phase (with screenshots embedded as data: URIs), and the open-items / next-action block. It is the human-readable face of the evidence ledger.

  • Template: ../closed-loop/references/report-template.html (theme-aware, rows-not-cards). Copy it, then fill every {{token}} and <!-- FILL --> / <!-- REPEAT --> block from spec.md + STATUS.md + evidence/P*/. You fill it by editing; do not build a parser.
  • Deliverable path: 04-projects/<goal>/report.html. One file, overwritten each phase (it always reflects current truth).
  • When: regenerate at each phase gate (CP-6) and again at final north-star acceptance. The final report must show every AC-n with a PASS row — if any pill is open, the goal is not done.
  • Self-contained only: inline everything, embed screenshots as data: URIs, so it also works when published as an Artifact (external hosts are blocked). Before publishing as an Artifact, load the artifact-design skill.
  • Surface it: SendUserFile 04-projects/<goal>/report.html (display: render) so the user can open it, or publish via Artifact for a shareable link.

STATUS.md template

markdown
# <Goal> — status ledger

North-star: <one sentence>
Spec: 04-projects/<goal>/spec.md · Registry: 04-projects/harness/ultragoals.md
Current phase: P<n> · Overall: <not-started|in-progress|blocked|done>

## Phases
| Phase | AC covered | State | Evidence | Notes |
|---|---|---|---|---|
| P0 | AC-1,AC-2 | done | evidence/P0/ | <one line> |
| P1 | AC-3 | in-progress | evidence/P1/ | <what's left> |

## Open AC-n (no PASS row yet)
- AC-3 — <why still open>

## Next action (resume cold from here)
<the single next concrete step + any user-gated decision waiting>

Resuming cold (most common entry)

/ultragoal <name> with no other context:

  1. Read 04-projects/<goal>/STATUS.md → "Next action" and "Open AC-n".
  2. Read the spec's phase for the current phase only (progressive disclosure).
  3. Run the phase loop for the current phase.
  4. Never re-do a phase already marked done unless integration verify caught a regression.

Rules

  • Never downgrade the lane. Even a one-line phase inside an ultragoal runs CP-3v + CP-4. The point is compounding correctness.
  • UI/UX phases verify visually. If a phase touches a UI/UX flow, capture rendered evidence with browser-harness (evidence_shot / FlowRecorder.save_gif / pixel_diff), read the image, fix any visual defect, and re-capture — do not accept a DOM check. Media lands in evidence/P<n>/ and feeds report.html. See CLAUDE.md → Visual Verification.
  • Fresh-context verifiers. task-verifier, integration-verifier, north-star verifier get paths only — never paste worker output in (CLAUDE.md fresh-context isolation).
  • Read-only verifiers. They cannot edit files or mutate external state.
  • Gate all external. Any publish / deploy / push waits at CP-6 for the user (Review Gate = your approval).
  • One STATUS.md is the source of truth for where the goal stands. Update it at the end of every phase or it drifts.
  • Model routing per CLAUDE.md: Sonnet workers build/collect/verify; Opus lead reasons, decomposes, synthesizes.

Escalation template

ULTRAGOAL ESCALATED — <goal> / P<n>
Last CP: <CP-id> | Open AC: <list without PASS rows>
Evidence: 04-projects/<goal>/evidence/P<n>/
Decision needed: <one question>

Registered ultragoals

Live list: 04-projects/harness/ultragoals.md. Each ultragoal gets its own 04-projects/<goal>/ folder holding spec.md, STATUS.md, evidence/, and report.html.

Frequently asked questions

What does the Ultragoal AI skill do?

Run a large, multi-session goal (e.g. shipping a whole side product) through the full V-model closed loop, one phase at a time, with cross-session state and a final north-star acceptance gate. Ultragoals never downgrade the lane: every phase runs CP-1→CP-6 with adversarial verification. Opt-in: invoke with /ultragoal or by calling something a long-running goal. Ordinary work does not run this.

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/huytieu/COG-second-brain/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 huytieu 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇