neura-openclaw-browser-action-review

neura-openclaw-browser-action-review is a skill for Claude Code, Codex from neurarelay/relay-action-card. It costs 46 tokens per session (227 once invoked), scanned A, original, MIT.

A review step for browser actions that submit forms or change state, such as purchases or account updates. It creates a decision record from references before the action is sent.

In plain words
What is it for?
Preparing approval records for browser form submissions, purchases, account changes, and other state-changing automation.
Why use it?
It helps verify that the target, user intent, entered values, policy, authority, and risk have been checked before a consequential browser action.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Preparing approval records for browser form submissions, purchases, account changes, and other state-changing automation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/neurarelay/relay-action-card/neura-browser-action-review
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.

Any agent
npx skills add neurarelay/relay-action-card --skill neura-browser-action-review
Clone the repo
git clone --depth 1 https://github.com/neurarelay/relay-action-card

Made for: Claude Code, 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 neura-openclaw-browser-action-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/neurarelay/relay-action-card/neura-browser-action-review/github.svg)](https://agentmods.dev/skills/neurarelay/relay-action-card/neura-browser-action-review)
Your own site
<a href="https://agentmods.dev/skills/neurarelay/relay-action-card/neura-browser-action-review"><img src="https://agentmods.dev/badge/skills/neurarelay/relay-action-card/neura-browser-action-review/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.

agentmods 80×15 button for neura-openclaw-browser-action-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/neurarelay/relay-action-card/neura-browser-action-review"><img src="https://agentmods.dev/badge/skills/neurarelay/relay-action-card/neura-browser-action-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 227 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00046 $0.00227
Opus 5.5 $0.00018 $0.00091
Sonnet 5.5 $0.00009 $0.00045
Haiku 4.5 $0.00005 $0.00023

Measured 1mo ago against content hash dc1500523235, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neura-openclaw-browser-action-review 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.

skills/openclaw/neura-browser-action-review/SKILL.md · 24 lines

What it actually says

Neura Browser Action Review

Use this skill before browser submits, purchases, account changes, or other state-changing web actions. Create a refs-only Action Card and get a Decision Receipt before dispatch.

This is an example skill, not an official OpenClaw or ClawHub integration, listing, approval, or partnership.

Check

  • target page or form ref is present
  • user intent ref is present
  • field-value refs are present without raw sensitive values
  • rule or policy ref covers the proposed browser action
  • delegated authority covers the target site/action family
  • risk category reflects money movement, account state, customer impact, or data access

Output

Return a Decision Receipt-ready Action Card draft, missing refs, and the suggested route. Do not submit the form, click the state-changing control, expose browser secrets, or include raw form values.

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. 1mo ago First seen · 24 lines · 46 tokens per session scan A dc1500523235

Subscribe to this mod's changes

neura-openclaw-browser-action-review is a skill published in the GitHub repository neurarelay/relay-action-card (2 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 227 once invoked, about $0.0002 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 2026-08-31.

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