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.
npx skills add KonghaYao/peri --skill ultracodegit clone --depth 1 https://github.com/KonghaYao/periWrote 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.
[](https://agentmods.dev/skills/konghayao/peri/ultracode)<a href="https://agentmods.dev/skills/konghayao/peri/ultracode"><img src="https://agentmods.dev/badge/skills/konghayao/peri/ultracode.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.02127 |
| Opus 5 | $0.00029 | $0.01064 |
| Sonnet 5 | $0.00012 | $0.00425 |
| Haiku 4.5 | $0.00006 | $0.00213 |
Grade A, and why
ultracode 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ultracode: Multi-Agent Workflow Orchestration
You have access to the Workflow tool (via SearchExtraTools → ExecuteExtraTool), which lets you orchestrate multiple agents working in parallel or pipeline phases.
When to Use
Use the Workflow tool when:
- The task can be decomposed into independent parallel subtasks
- The task benefits from a pipeline (phased execution where later phases depend on earlier results)
- You need to explore multiple approaches simultaneously
- The user explicitly asks for "ultracode", "workflow", or parallel execution
Do NOT use workflows for:
- Simple single-agent tasks (just do the work directly)
- Tasks requiring tight sequential conversation (use normal tool calls)
- Tasks that are faster to do inline than to script
How to Use
1. Discover the Workflow tool
The Workflow tool is a deferred tool. First search for it:
SearchExtraTools("workflow")
Then execute it:
ExecuteExtraTool("Workflow", {
"script": "...your workflow script...",
"args": {},
"maxConcurrency": 3
})
2. Write a workflow script
Workflow scripts are JavaScript ESM modules using these primitives:
agent(prompt, options?)— Run a single agent. Returns the agent's output.parallel([...factories])— Run multiple agents concurrently. 入参为返回 promise 的零参工厂函数(thunks),不是 promise。 Returns array of results.pipeline(items, ...stages)— 数据流水线:对 items 每个元素顺序执行所有 stage,stage=(prev, item, index) => result,stage 的返回值为下一个 stage 的 prev。返回与 items 等长的数组,出错位置为 null。phase(title)— 切换当前阶段标记(发 phase_started/done 事件),后续 agent 自动带该阶段名。不接 fn,返回 undefined。log(message)— Emit a log message visible in the workflow panel.workflow(nameOrScriptPath, args?)— 运行子 workflow(一层嵌套上限)。workflow('sub-name', args)按名字查找,workflow({ scriptPath: '...' }, args)按文件路径加载。
3. Example: Parallel Code Review
export const meta = {
name: 'parallel-review',
description: 'Review code from multiple perspectives in parallel'
}
const [security, perf, bugs] = await parallel([
() => agent('Review this code for security vulnerabilities. Focus on injection, auth, and data exposure.', { label: 'security', allowedTools: ['Read', 'Grep'] }),
() => agent('Review this code for performance issues. Focus on N+1 queries, unnecessary allocations, and hot paths.', { label: 'performance', allowedTools: ['Read', 'Grep'] }),
() => agent('Review this code for bugs. Focus on edge cases, error handling, and logic errors.', { label: 'bugs', allowedTools: ['Read', 'Grep'] }),
])
return { security, perf, bugs }
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.
- 7d ago First seen · 182 lines · 58 tokens per session scan A d06e3fa9da49
ultracode is a skill published in the GitHub repository KonghaYao/peri (160 stars, last pushed 2d ago), licensed Apache-2.0. It adds 58 tokens to every session and 2,127 once invoked, about $0.0003 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.
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