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Jev Agent Integration Playbook
Jev Wiki's Steps 0-7 playbook for a coding agent told to build with Jev: decide whether Jev fits, decompose the job into atomic questions, shape state, call POST /v1/systemone, and branch on confidence.
- Format
- Docs
- Reading time
- 2 min
- Published by
- Community
- Author
- Jev Wiki
- Last verified
- Oct 2026
- Languages
- PythonJavaScript
Highlights
- Covers Steps 0-7: fit check, decomposition, state shaping, question writing, access and calling, consuming answers, error handling, and testing.
- Pins Python SDK 0.7.5 and JavaScript SDK 0.7.0, with jev_version recorded as 1.13.0 at the 2026-10-15 update.
- Direct signup reopened 2026-09-27 with no free credits for new signups; gateway routes are offered as an alternative in Step 4.
- Images and box on Jev 1.14 are experimental behind TypeSafe-Danger-Zone-Images: true, and the page says to tell the user first.
- Long context sits behind TypeSafe-Danger-Zone-Long-Context: true at 262k and is described as slower and less accurate.
Watch out
A community wiki page, marked high confidence but not vendor documentation, and it says TypeSafe's live docs win any conflict. Its skill-install commands change other projects, so it tells agents to ask the user first; no licence is stated for its text. Images, box, and long context are experimental and should not be described as production-ready.
Questions about this entry
Short answers drawn from the linked project or page.
A coding agent told to use Jev for a task reads it end to end: it walks through fit checking, splitting a job into atomic questions, filtering state, writing questions, getting access, calling POST /v1/systemone, consuming answers, handling errors, and testing.
Noul returns one probability; Choice returns a choice plus probabilities and confidence; Score returns a score plus probabilities and confidence. System One never generates text, does arithmetic, or picks its own next action, so those stay in code.
Text generation, summaries, and code go to an LLM; arithmetic, counting, date logic, regexes, lookups, and exact thresholds go to code; audio and video need pre-processing to text. Images are for prototypes only, behind the danger-zone header.
Step 4 covers access: direct signup reopened on 2026-09-27 with no free credits for new signups, and the step also documents the gateway route for teams already behind a platform.
Claude Code users add the marketplace and install typesafe@typesafe-ai; other agents run npx skills add typesafe-ai/skills --skill typesafe-ai. The page tells agents to ask the user before installing anything into their project.
Jev reads text only, so audio and video must be pre-processed. Images and box on 1.14 are experimental behind TypeSafe-Danger-Zone-Images: true, and the page says TypeSafe itself does not call them ready for production.
A request carries up to 64k tokens, with 32k for state plus the longest question. The experimental long-context header raises both caps to 262k but is documented as slower and less accurate.
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