ultrawork

ultrawork is a skill for Codex from Orinks/AccessiWeather. It costs 18 tokens per session (2,042 once invoked), scanned A, original, MIT.

A parallel task-execution method for handling independent coding tasks at the same time.

In plain words
What is it for?
Use it for multiple independent tasks or when you explicitly want parallel execution with commands such as “ulw” or “ultrawork”.
Why use it?
It reduces waiting when separate pieces of work can be completed concurrently, while keeping a lightweight evidence check.

Skill for Codex

Written for Codex: installed under .codex/. Also seen: mentions Codex.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/orinks/accessiweather/ultrawork
Any agent
npx skills add Orinks/AccessiWeather --skill ultrawork
Clone the repo
git clone --depth 1 https://github.com/Orinks/AccessiWeather

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ultrawork

README.md
[![agentmods](https://agentmods.dev/badge/skills/orinks/accessiweather/ultrawork.svg)](https://agentmods.dev/skills/orinks/accessiweather/ultrawork)
Your own site
<a href="https://agentmods.dev/skills/orinks/accessiweather/ultrawork"><img src="https://agentmods.dev/badge/skills/orinks/accessiweather/ultrawork.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,042 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.02042
Opus 5 $0.00009 $0.01021
Sonnet 5 $0.00004 $0.00408
Haiku 4.5 $0.00002 $0.00204

Measured 6d ago against content hash 75a51501b3b5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

ultrawork scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.codex/skills/ultrawork/SKILL.md · 176 lines

How it starts

The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Use_When>

  • Multiple independent tasks can run simultaneously
  • User says "ulw", "ultrawork", or explicitly wants parallel execution
  • Task benefits from concurrent execution plus lightweight evidence before wrap-up
  • You need a direct-tool lane plus optional background evidence lanes without entering Ralph </Use_When>

<Do_Not_Use_When>

  • Task requires guaranteed completion with persistence, architect verification, or deslop/reverification -- use ralph instead (Ralph includes ultrawork)
  • Task requires a full autonomous pipeline -- use autopilot instead (autopilot includes Ralph which includes ultrawork)
  • There is only one sequential task with no parallelism opportunity -- execute directly or delegate to a single executor
  • The request is still in plan-consensus mode -- keep planning artifacts in ralplan until execution is explicitly authorized
  • User needs session persistence for resume -- use ralph, which adds persistence on top of ultrawork </Do_Not_Use_When>

<Why_This_Exists> Sequential task execution wastes time when tasks are independent. Ultrawork keeps the execution branch fast while tightening the protocol: gather enough context first, define pass/fail acceptance criteria before editing, decide deliberately between local execution and delegation, and finish with evidence rather than vibes. </Why_This_Exists>

<Execution_Policy>

  • Gather enough context before implementation. Start with the task intent, desired outcome, constraints, likely touchpoints, and any uncertainty that would change the execution path.
  • If uncertainty is still material after a quick repo read, do a focused evidence pass first instead of immediately editing.
  • Define pass/fail acceptance criteria before launching execution lanes. Include the command, artifact, or manual check that will prove success.
  • Prefer direct tool work when the task is small, coupled, or blocked on immediate local context. Delegate only when the work is independent enough to benefit from parallel execution.
  • When useful, run a direct-tool lane and one or more background evidence lanes at the same time. Evidence lanes can cover docs, tests, regression mapping, or bounded repo analysis.
  • Fire independent agent calls simultaneously -- never serialize independent work.
  • Always pass the model parameter explicitly when delegating.
  • Read docs/shared/agent-tiers.md before first delegation for agent selection guidance.
  • Auto-delegate researcher when official docs, version-aware framework guidance, best practices, or external dependency behavior materially affect task correctness; treat it as an evidence lane, not a replacement primary workflow.
  • Use run_in_background: true for operations over ~30 seconds (installs, builds, tests).
  • Run quick commands (git status, file reads, simple checks) in the foreground.
  • Apply the shared workflow guidance pattern: outcome-first framing, concise visible updates for speculative/blocked lanes, local overrides for the active workflow branch, evidence-backed validation, explicit stop rules, and continuation of clear safe execution branches instead of restarting or re-asking.
  • If the user says continue, continue the active workflow branch rather than restarting discovery or re-asking settled questions. </Execution_Policy>

Read the full file on GitHub · 176 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 176 lines · 18 tokens per session scan A 75a51501b3b5

Subscribe to this mod's changes

ultrawork is a skill published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed 12d ago), licensed MIT. It adds 18 tokens to every session and 2,042 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens