jev-act
GitHub用于在浏览器、桌面、游戏或模拟环境中选择下一个合法动作的 Agent 技能。支持真实 API 调用与模拟模式,提供安全决策流程、依赖检查及上下文管理,确保动作选择的合规性与准确性。
Trigger Scenarios
Install
npx skills add wuyoscar/jev-skill --skill jev-act -g -y
SKILL.md
Frontmatter
{
"name": "jev-act",
"description": "Choose one legal next action in a browser, desktop, game or simulation. Supply fresh observed state and available actions. The host or simulator executes and checks the result; selection does not grant permission."
}
Choose the next action
Learn from the workflows
For design requests, browse the scenario index, read the relevant guides and input/output examples, and compare or combine patterns. Adapt what you learn to the user's task; the collection is inspiration, not a closed menu. A familiar, straightforward decision can use its recipe directly.
Friendly reminder: Jev can help with initial, repeated or bulk judgments while you lead the overall work. Read the evidence, design the workflow, spot-check results (including confident or agreeing labels), and bring your own analysis and synthesis. This is guidance for collaboration, not an agent harness or a fixed call/token quota; existing user permissions and budgets still apply.
Use safely
Choose the service once and keep that choice. If unset, ask A: real Jev via
OpenRouter (OPENROUTER_API_KEY) or TypeSafe (TYPESAFE_API_KEY), or B: simulation
with this agent or an explicitly chosen available model such as DeepSeek. Wait for
consent; errors do not authorize switching. Check key presence only, never values.
Real calls send evidence and cost money; get approval before sending private data.
For B, skip CLI/API calls. Mark agent_simulation or model_simulation, identify
the actual model when available, set jev_called: false, probability: null and
confidence: null. Return a value, evidence-based reason and needs_review; use
null/review when evidence is missing. Do not invent Jev output or probabilities.
Choice uses supplied labels, Noul uses booleans, Score uses integer rubric indices.
For A, use the existing jev-decide CLI with the chosen --provider openrouter
or --provider typesafe. If absent, explain the dependency; do not silently install.
--dry-run is offline validation, not a judgment. Exit 0 means selected/scored,
2 means review, 1 means error. Read each value: false Noul remains false. Selection
is not permission, and confidence is not accuracy. Keep unknown/review paths.
First request
Adapt the example. The shared CLI needs Python 3.10+;
no sibling skill is needed. Host tools still own collection and actions.
Resolve <skill-dir> to this installed folder:
jev-decide decide <skill-dir>/assets/example.json --dry-run
# After approval, send the edited request with the selected provider:
jev-decide decide /path/to/request.json --provider openrouter
Pick one mode
- Browser or desktop: read UI steps; start with the UI request.
- Game or simulation: read world steps; start with the world request.
Use only the current mode. A simulated world is not permission to operate a real account. The host validates legal actions, checks freshness and applies the result.
Context and parallelism
Jev does not inherit the agent's history. Include the goal, rules, fresh context, legal candidates and relevant outcomes. Batch independent checks in the same request. Use bounded concurrency only for independent requests; the host owns scheduling. Wait for a new observation after an action before asking a dependent question.
Examples
Next browser action · Browser wait versus intervention · Browser outcome verification
More workflows and local templates. Browse across examples when designing a solution; follow the guides and sources that help.
Version History
- 7154e95 Current 2026-09-27 10:20


