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Build a Pi extension as a TypeScript or JavaScript module whose default export is a factory receiving Pi’s ExtensionAPI. Put each Jev decision at the hook that can still affect the outcome: route before model work, gate a tool call before execution, and screen a tool result after it returns. Start in shadow or advisory mode, define what happens when Jev fails, then test decision logic, hook effects, and a controlled run through the Pi CLI.
What a Pi extension with Jev can do
Pi extensions add executable behavior to the coding agent. An extension can register tools, commands, event handlers, providers, session state, or terminal UI. Jev can supply typed decisions for tasks such as model routing, tool-call supervision, or screening returned content. The official Pi extensions documentation describes the extension entry point and development loading; the pi-jev project documents example Jev integrations.
The basic shape is a default-exported factory. Start locally with pi --extension ./extension.ts; Pi’s documentation also describes package-based distribution. Check the current documentation for exact API signatures and package requirements because the page and implementation can change.
export default function (pi) {
pi.on("before_agent_start", async (event, ctx) => {
// Make a decision before model work only when this hook fits the policy.
return undefined;
});
}This is a structural sketch, not a complete Jev client: use the current Pi and Jev interfaces for event types, decision requests, and returned values. Do not start processes, sockets, watchers, or timers in the factory. Pi documents that some invocations load extensions without starting a session, so create long-lived resources from session_start or only when the action needing them occurs.
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Choose the hook by when the decision must take effect
Pi’s run can involve more than one simple prompt-and-response cycle: retries, recovery, compaction, and queued work may continue after an apparent turn boundary. Select a hook based on the point at which your policy must act, not merely where it is easiest to call Jev.
| Decision | Useful hook | Effect timing |
|---|---|---|
| Influence model choice or the turn before model work | before_agent_start |
Before the model does the turn’s work |
| Allow, block, or supervise a tool invocation | tool_call |
Before the tool executes |
| Screen or transform returned tool content | tool_result |
After the tool has already run |
| Observe later turn or run outcomes | Turn-end or agent_end events |
After the relevant work; useful for observation, not prevention |
The hook mappings are described by Pi’s documentation and the pi-jev repository. Verify the exact current event names, arguments, and return contract before implementing; APIs evolve. Close session-scoped resources through an idempotent shutdown handler so repeated cleanup does not leave the extension in a broken state.
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Decide whether Jev advises, blocks, or changes behavior
Keep decision mode explicit. The pi-jev project describes modules that are shadow by default or disabled: they log decisions without changing agent behavior until promoted. Its /jev command provides status, explanation, module toggles, and a kill switch. Shadow mode is useful while reviewing classifications because it separates observing a policy from enforcing it.
The pi-typesafe example distinguishes advisory checks from blocking checks. Advisory feedback is recorded and appended after execution, so it cannot prevent a hazardous side effect. Blocking mode can refuse qualifying hazards before they execute. For security-sensitive actions, a post-execution warning is not a substitute for a pre-execution gate.
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Define unavailable and malformed-response behavior
Decide in advance what the extension does on timeout, authentication failure, rate limiting, transport errors, or an invalid Jev answer. For consequential tool calls, an explicit fail-closed policy can avoid silently allowing a risky action when no valid judgment exists, but it can also interrupt legitimate work when Jev is unavailable. For less consequential routing or screening, a documented fallback may preserve usability. Do not treat a project’s particular failure policy as a guarantee for every Jev integration.
Make deterministic rules legible and reserve semantic judgment for cases that need it. The auto-mode project describes a deterministic policy layer before semantic judgment and fail-closed handling when a decision cannot be made; those are design choices, not universal properties of extensions. Keep the decision threshold and fallback visible in code and logs so operators can explain why an action was allowed, denied, or left unchanged.
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Bound and protect what the extension sends
A decision service can only judge the context it receives, but sending more context than necessary increases exposure. Specify which fields leave the Pi process, how much conversation or tool output is included, and what must be redacted or omitted. Bound payload size and apply timeouts; avoid forwarding secrets, credentials, or unrelated session history. The cited project material establishes example integrations, but does not define one universally safe payload policy, so choose limits for the data and threat model of your extension.
Quick wins for a faster PC:
Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Review extension code before installing it. Pi’s package gallery warns that packages can execute code and influence agent behavior. That applies to the extension’s local privileges and to any external services it contacts, not just to the quality of its Jev decisions.
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Test logic first, then prove hook effects
A helper returning the expected decision does not prove that Pi will block a tool or switch a model. Test in increasing realism so a failure points to the layer that needs attention.
- Unit tests: cover decision tables, thresholds, boundary values, and invalid or missing answers. Include cases just below, at, and above each threshold.
- Fake Pi harness: invoke the registered hook and assert the returned effect, not just the Jev helper result. For example, assert that a model selection changes, a qualifying tool call is confirmed or blocked, or a result is replaced when screening applies.
- Local Jev-protocol server: exercise success as well as timeout, authentication, rate-limit, malformed-response, and server-error paths. Assert that the extension follows its chosen fallback policy.
- Real Pi CLI run: run Pi with the extension and controlled local mock model and judgment services. Use a harmless, reproducible prompt or tool action and verify the resulting event and side effect. The pi-jev project describes offline end-to-end runs against local mocks.
The pi-jev project reports tests at these levels, including a fake Pi harness and offline end-to-end runs. These are project-reported tests, not independent validation. Keep mock services local and controlled so the run is repeatable and does not depend on a live judgment endpoint.
What the published Jev fixture numbers do—and do not—show
The following figures are the pi-jev project’s own v0 labeled-fixture results, accessed in 2026. They are small project-authored samples, not an independent benchmark or a prediction of production performance.
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| Measure | Project-reported result | How to interpret it |
|---|---|---|
| Router tier accuracy | 90–92% across fixture runs | Fixture performance only; production workloads may differ. |
| Router added latency | 288–673 ms p50, load-dependent | Reported for the project’s fixture runs, not a general service-latency guarantee. |
| Dangerous-command gate false negatives | 0/19 | No missed dangerous command in this 19-case fixture sample; this does not establish zero risk. |
| Safe-command gate false positives | 5.0% (1/20) | One safe command was flagged in the 20-case fixture sample. |
| Shield injection detection | 93.3% (14/15) | Detection in a 15-case fixture sample, not broad security assurance. |
The project says router net model-cost change, real-session gate cache hit rate, and prune token savings were not measured. Those figures should not be inferred from accuracy or fixture results.
Quick Recap
Promote cautiously and keep an operational escape route
- Run shadow mode first and inspect decisions against real, representative sessions before enforcing them.
- Review false positives as well as false negatives; a gate that blocks too much can disrupt normal work even if it catches some hazards.
- Enable blocking only for the decision points where prevention matters, and retain a kill switch or clear way to disable the module.
- Monitor timeouts and malformed decisions, and ensure logs do not expose secrets or unnecessarily retain sensitive prompt and tool content.
- Recheck Pi hook signatures, package identity, and Jev behavior as the rolling documentation and repositories change.
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