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 PeakCode-AI/PeakCode --skill jev-ultrafastgit clone --depth 1 https://github.com/PeakCode-AI/PeakCodeWrote 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/peakcode-ai/peakcode/jev-ultrafast)<a href="https://agentmods.dev/skills/peakcode-ai/peakcode/jev-ultrafast"><img src="https://agentmods.dev/badge/skills/peakcode-ai/peakcode/jev-ultrafast/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/peakcode-ai/peakcode/jev-ultrafast"><img src="https://agentmods.dev/badge/skills/peakcode-ai/peakcode/jev-ultrafast.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.01316 |
| Opus 5.5 | $0.00013 | $0.00526 |
| Sonnet 5.5 | $0.00006 | $0.00263 |
| Haiku 4.5 | $0.00003 | $0.00132 |
Grade A, and why
jev-ultrafast 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 1mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jev Ultrafast
browser-use covers the mechanics — snapshots, refs, coordinates, permissions, the
observe/act/observe loop. This is the decision policy on top of them: how to choose the next
action so that a run spanning dozens of steps still finishes quickly.
It comes from browser-use/jev-ultrafast, where a goal runs on an indexed action space: one observation, one decision, one action, with the operation and its target chosen together.
One table, one decision, one action
Take a snapshot, then write the candidates out once as a numbered table — one index per
element, the value it currently holds, and the operations it can take:
[1] e3 button "Change ticket type · Round trip"
[2] e5 combobox "Where from?" value="San Francisco"
[3] e7 combobox "Where to?" value=""
[4] e9 textbox "Departure" value=""
[5] e12 button "Search"
Then choose the operation and its target in the same step, and make one tool call. Two decisions, one observation: the target cannot come from a table the operation did not see, and a step costs one snapshot instead of two.
The numbering is the point, not decoration. One index per element makes a checkbox and its label one target instead of two, and each line carries the current value — so "is this step already done" is answered by the table rather than by memory.
Do not take a fresh snapshot between deciding and acting. Reuse the one you have: that single observation per step is what makes the loop fast, and it stays valid until the page changes.
The index is local to its snapshot, like the ref it points at. When the page moves, rebuild the
table; never carry an index across observations, and never act on an element that was not in
the table. If the snapshot reports elements omitted by its cap, the control you want may be
past it — raise max_elements or scroll to it rather than guessing at a target.
Match the operation to the element
Only three operations change a page, and each takes its own kind of target:
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.
- 1mo ago First seen · 110 lines · 0 tokens per session scan A e8096824cec7
jev-ultrafast is a skill published in the GitHub repository PeakCode-AI/PeakCode (142 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 1,316 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-19.
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