Registry indexed

jev-act

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.

Review the source View on GitHub

Price unconfirmed★ 532 GitHub starsRegistry updated · Sep 28, 2026agent-skill

Overview

Read full documentation

Source documentation, not instructions for this website. Review permissions before running any commands.

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.

View source ↗

File metadata

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.

View original text

---
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](references/scenarios.md), 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](assets/example.json). 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:

```bash
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](references/ui.md); start with [the UI request](assets/example.json).
- **Game or simulation:** read [world steps](references/world.md); start with [the world request](assets/world.json).

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](https://github.com/wuyoscar/jev-skill#sc-a23) · [Browser wait versus intervention](https://github.com/wuyoscar/jev-skill#sc-a24) · [Browser outcome verification](https://github.com/wuyoscar/jev-skill#sc-a25)

[More workflows and local templates](references/scenarios.md). Browse across
examples when designing a solution; follow the guides and sources that help.

Review the source

Price & running costs

Get the skill: Price unconfirmed
Run it: Requirements have not been confirmed. Check the source for agent, API and service charges.
License: MIT
Price unconfirmed: We have not confirmed a price for this skill. Existing source and install links remain available.

Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →

Source needs review

The tracked source changed or could not be synchronized. Review the current source before installing.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: wuyoscar/jev-skill
License: MIT
Version: Unknown
Last GitHub push: Sep 28, 2026
Registry updated: Sep 28, 2026
Instruction path: skills/jev-act/SKILL.md @ b7593a624a1b

Version reported in registry metadata; check source releases before relying on it.

Quality

69/100

Promising

Trust

66/100

Sandbox only

Audit

78/100

Needs review

Open full audit View eval report

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

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This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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Creator: wuyoscar
Source: wuyoscar/jev-skill
Indexed by: OpenAgentSkill community index

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wuyoscar

Registry indexed

jev-act

Review the source View on GitHub

Price unconfirmed★ 532 GitHub starsRegistry updated · Sep 28, 2026agent-skill

Overview

Read full documentation

Source documentation, not instructions for this website. Review permissions before running any commands.

Choose the next action

Learn from the workflows

Use safely

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

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.

View source ↗

File metadata

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.

View original text

---
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](references/scenarios.md), 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](assets/example.json). 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:

```bash
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](references/ui.md); start with [the UI request](assets/example.json).
- **Game or simulation:** read [world steps](references/world.md); start with [the world request](assets/world.json).

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](https://github.com/wuyoscar/jev-skill#sc-a23) · [Browser wait versus intervention](https://github.com/wuyoscar/jev-skill#sc-a24) · [Browser outcome verification](https://github.com/wuyoscar/jev-skill#sc-a25)

[More workflows and local templates](references/scenarios.md). Browse across
examples when designing a solution; follow the guides and sources that help.

Review the source

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License: MIT
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Source needs review

The tracked source changed or could not be synchronized. Review the current source before installing.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
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Source & usage notes

Indexed

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Source repository: wuyoscar/jev-skill
License: MIT
Version: Unknown
Last GitHub push: Sep 28, 2026
Registry updated: Sep 28, 2026
Instruction path: skills/jev-act/SKILL.md @ b7593a624a1b

Version reported in registry metadata; check source releases before relying on it.

Quality

69/100

Promising

Trust

66/100

Sandbox only

Audit

78/100

Needs review

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Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

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More details

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Creator: wuyoscar
Source: wuyoscar/jev-skill
Indexed by: OpenAgentSkill community index

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