Borrowing it
Nothing to install: this file belongs to EastStarAI/sanad-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/EastStarAI/sanad-agent/main/.agents/skills/jev-dual-brain-automation/SKILL.mdgit clone --depth 1 https://github.com/EastStarAI/sanad-agentWrote 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/eaststarai/sanad-agent/jev-dual-brain-automation)<a href="https://agentmods.dev/skills/eaststarai/sanad-agent/jev-dual-brain-automation"><img src="https://agentmods.dev/badge/skills/eaststarai/sanad-agent/jev-dual-brain-automation/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/eaststarai/sanad-agent/jev-dual-brain-automation"><img src="https://agentmods.dev/badge/skills/eaststarai/sanad-agent/jev-dual-brain-automation.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 | $0.00105 | $0.01880 |
| Opus 5.5 | $0.00042 | $0.00752 |
| Sonnet 5.5 | $0.00021 | $0.00376 |
| Haiku 4.5 | $0.00011 | $0.00188 |
Grade A, and why
jev-dual-brain-automation 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jev Dual-Brain Automation
Use Jev as a fast judgment primitive inside a workflow owned by software. Jev is not an agent: it does not own phases, retries, irreversible actions, arithmetic, dates, safety policy, or completion.
Ownership model
| Owner | Responsibilities |
|---|---|
| Deterministic code | Phase order, structured state, candidate IDs, thresholds, exact dates/numbers, action execution, irreversible-action admission, event subscriptions, timeouts, assertions, and audit history |
| Jev (System 1) | One narrow semantic Choice, Score, or Noul judgment over supplied state |
| System 2 | Diagnose blockers, ambiguity, unknown screens, low confidence, oscillation, and policy-sensitive decisions |
| UI adapter | Observe the current surface and execute an exact action selected by code |
Do not ask Jev to “complete the task,” infer a multi-step plan, calculate totals, compare exact dates, or decide whether a risky action is allowed. Ask one snap judgment per question and compose the answers in code.
Required workflow
- Define phases before acting. Mark submit, send, purchase, delete, permission, and similar effects as irreversible.
- Observe structured state. Include the goal, current phase, screen/page mode, relevant candidates, completed phases, and bounded action history as named JSON fields.
- Prune candidates deterministically. Send stable IDs and concise descriptions. Never let Jev invent a selector.
- Classify hierarchically when decisions depend on each other. First classify page/screen mode. In a later request, ask for the action among candidates valid for that mode. Questions in one request are independent; one answer cannot condition another answer in the same batch.
- Inspect the complete answer. Choice and Score return probabilities plus confidence. Route low confidence or an invalid target to System 2 before acting. Noul is itself a yes probability and has no separate confidence field.
- Reserve the phase before an irreversible action. A completed phase cannot re-enter. An attempted irreversible phase cannot be retried automatically after an ambiguous result.
- Snapshot immediately before acting. Execute one exact adapter action, once.
- Wait for events, not repeated model calls. Subscribe to navigation, lifecycle, response, or UI-transition events and block until a relevant event or timeout. Do not poll Jev while waiting.
- Verify after the event. Use deterministic assertions for exact strings, IDs, dates, counts, and numeric values. Use a separate narrow Jev judgment only for semantic evidence.
- Escalate fail-closed. Stop on low confidence, blockers, invalid candidates, unchanged UI, repeated targets, oscillation, timeout, or unknown state. Give System 2 bounded state, candidates, phase ledger, and recent actions.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 3.9 KB
- references/api_reference.md 4.4 KB
- references/failure_modes_and_recovery.md 4.7 KB
- scripts/dual_brain_browser.py 2.3 KB runs code
- scripts/jev_client.py 16 KB runs code
- scripts/workflow_engine.py 7.4 KB runs code
- tests/test_jev_client.py 18 KB runs code
- tests/test_skill_contract.py 2.8 KB runs code
- tests/test_workflow_engine.py 4.4 KB runs code
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 Changed · -13 lines ab3ade5b9de1
- 1mo ago Changed · +2 lines · -29 tokens per session 6d64e2da1676
- 1mo ago First seen · 160 lines · 134 tokens per session scan A cd0b58cbca06
jev-dual-brain-automation is a skill published in the GitHub repository EastStarAI/sanad-agent (47 stars, last pushed yesterday), licensed MIT. It adds 105 tokens to every session and 1,880 once invoked, about $0.0004 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 2026-09-22.
jev-dual-brain-automation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| jev-dual-brain-automationEastStarAI/sanad-agent | Skill | 47 | yesterday | MIT | A | 105 | Claude Code, Codex |
| e2esgaabdu4/building-flutter-apps | Skill | 25 | 4d ago | MIT | A | 42 | Claude Code, Codex |
| flutter-mcp-automation-chainArenukvern/mcp_flutter | Skill | 395 | 20d ago | MIT | C | 176 | Claude Code |
| simpodcscoderr/simpod | Skill | 27 | 4mo ago | Apache-2.0 | A | 63 | Claude Code, Codex |
| flutterpledgeandgrow/pledge-skills | Skill | 10 | 3mo ago | MIT | A | 126 | Claude Code, Codex |
| webapp-testingHmbown/CodeWhale | Skill | 41k | 5d ago | MIT | A | 32 | Claude Code, Codex |
| computer-usebojieli/ai-agent-book | Skill | 57k | 29d ago | Apache-2.0 | A | 139 | Claude Code, Codex |