ultrawork
Skill1 starsChanged 7 months agoMITView on GitHub
Maximum effort mode — full pipeline from exploration to shipped, verified PR
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
When quality matters more than speed
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
ultrawork
The highest-rigor execution mode. Runs the full omc workflow end-to-end with no shortcuts.
Sequence
@explore → @deep-interview → @ralplan → @tdd/@ralph → @review → @security-review → @qa → @pipeline → @git-master prep-prWhen to use
- High-stakes features (auth, payments, data migrations)
- When quality matters more than speed
- Before major releases
When NOT to use
- Quick bug fixes → use
@ralphdirectly - Exploratory work → use
@explore+@autopilot
Example
@ultrawork "implement the payment processing flow"Hard stops:
@reviewFAIL → fix before continuing@security-reviewCRITICAL → fix before continuing (no exceptions)@pipelineFAIL after 2 cycles → surface to user
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- Yeachan-Heo/oh-my-codex★ 34ksame name
- zereight/gitlab-mcp★ 2.1ksame name
- first-fluke/fullstack-starter★ 223same name
- team-attention/hoyeon★ 173same name
- E4crypt3d/oh-my-qwen★ 9same name
- ibahgat/oh-my-iflow★ 2same name
- Jurel89/copilot-omni★ 0same name
- zephyrpersonal/oh-my-claude-code★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Used alongsideProjects with it also use ultraqa, ai-slop-cleaner and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
Jurel89Skillultraqa
QA cycling loop — build/lint/test, fix, retry up to 5 cycles
Also in 3 projects that use this
Jurel89Skillai-slop-cleaner
Clean AI-generated code slop with a regression-safe, deletion-first workflow and optional reviewer-only mode
Also in 3 projects that use this
BlockSkillplan
Draft a TDD, PRD, or lightweight plan in the conversation without committing it.
Also in 4 projects that use this
Microsoft AzureSkillverify
End-to-end app testing pipeline for browser-based web apps on cloud browsers via Azure Playwright Workspaces: verify the live app, author tests for working flows, heal failing tests, then re-run with video and produce one consolidated report. Three phases (app verification, test authoring, test healing) plus a scoped final sanity run; each phase emits a sub-report. Use when asked to "verify my app", "make sure my app works and has good test coverage", "do a full QA pass", "add tests where I'm missing coverage", "fix failing tests and add new ones", "smoke test before deploy", "QA my deployment", or any combined verify-and-test ask. Requires Azure CLI (`az login`) and a Playwright Workspace resource ID — bootstraps configs on first invocation. Browser-based web apps with Playwright only — not for unit/API tests, native mobile/desktop, load/perf, or full accessibility audits.
Also in 3 projects that use this
In this repository22 other files it gives its agents.
- analyzeSkill
- autopilotSkill
- cancelSkill
- carefulSkill
- chaosSkill
- checkpointSkill
- decision-reviewSkill
- deep-interviewSkill
- diagnoseSkill
- exploreSkill
- git-masterSkill
- incidentSkill
- noteSkill
- pipelineSkill
- qaSkill
- ralphSkill
- ralplanSkill
- resumeSkill
- reviewSkill
- security-reviewSkill
- tddSkill
- teamSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

