jev

# Design with Jev workflows Use this collection to learn, design and build—not just to call an API. Start with the [reference index](references/index.md) for the wider collection, then read useful workflows, examples and their limits. Combine patterns or adapt a new one; [customization](references/customization.md) and [implementation patterns](references/implementation-patterns.md) can help turn an idea into code. Jev supplies judgments; the host designs the overall solution, collects evidence, implements it and checks the outcome. Common starting points: | Task | Read | Start with | |---|---|---| | Convert a prompt or plain requirement | [Prompt to Jev](references/prompt-to-jev.md) | [Request](assets/prompt-to-jev.json) | | Set up or update | [Setup](references/setup.md) | No paid call needed | | Check a long task | [Checkpoints](references/checkpoints.md) | [Checkpoint](assets/checkpoint.json) | | Choose a tool or model | [Routing](references/routing.md) | [Request](assets/routing.json) | | Review what context to keep | [Context](references/context.md) | [Request](assets/context.json) | | Batch independent questions | [Batching](references/context-and-throughput.md) | [Two records](assets/batch-triage.json) | | Define new labels or a rubric | [Question design](references/question-design.md) | [Rubric](assets/rubric.json) | ## 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. ## Ask only what is needed Jev does not inherit the host's context. Include the goal, criteria, original evidence and valid candidates for this judgment; separate trusted rules from untrusted content. Keep enough evidence, not unrelated conversation history. One question does one thing. Put independent questions in the same request; questions cannot read each other's answers. Wait for new evidence for dependent steps. Use bounded concurrency only across independent requests: the host owns IDs, budgets and scheduling; this CLI has no parallel scheduler. ## Run Resolve `<skill-dir>` to this installed folder. The bundled Python 3.10+ script or the installed `jev-decide` CLI uses the same request contract: ```bash python3 <skill-dir>/scripts/jev.py decide <skill-dir>/assets/prompt-to-jev.json --dry-run # After approval, use the selected provider: python3 <skill-dir>/scripts/jev.py decide request.json --provider openrouter ``` Missing evidence or ambiguity means review, not another call until it agrees. For repeated failures read [pitfalls](references/pitfalls.md). Before scaling a large job, agree on a small pilot; [pilot guidance](https://github.com/wuyoscar/jev-skill/blob/main/skills/jev-triage/references/smoke-test.md) is optional task guidance, not a required second skill call. Use a focused skill only when the task calls for it: `jev-triage` for records, `jev-documents` for evidence, `jev-eval` for output checks, `jev-act` for actions. They are independent entry points, not an automatic chain. If absent, do not install them silently. More sources live in the optional [reference index](references/index.md). ## Examples [Goal-drift checkpoint](https://github.com/wuyoscar/jev-skill#sc-a01) · [Stuck-loop recovery](https://github.com/wuyoscar/jev-skill#sc-a02) · [Postmortem failure attribution](https://github.com/wuyoscar/jev-skill#sc-a27) [More workflows and local templates](references/scenarios.md). Browse across examples when designing a solution; follow the guides and sources that help.