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Build a Pi extension by exporting a default factory that receives ExtensionAPI, then attach each Jev decision to the Pi lifecycle hook where it can still affect the outcome. Start in shadow or advisory mode, make failure behavior explicit, and test from pure decision logic through a real Pi CLI session with local mocks.
What a Pi extension does
Pi extensions are TypeScript or JavaScript modules that add executable behavior to Pi. A default factory receives ExtensionAPI and can register tools, commands, event handlers, providers, session state, or terminal UI. Pi’s official extension documentation describes direct loading during development and package-based distribution.
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A minimal starting point is a module that exports a factory and registers one event handler:
export default function (pi) {
pi.on("session_start", async () => {
// Initialize session-scoped resources here.
});
pi.on("session_shutdown", async () => {
// Close resources safely; this may be called during shutdown.
});
}Load a local extension during development with pi --extension ./extension.ts. Confirm current API names and event signatures in the rolling official documentation before implementing; extension APIs and package metadata can change.
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Choose the hook based on when the decision matters
A decision is useful only if it runs before the effect it is meant to control. Pi’s run can involve input handling, agent startup, model and message events, tool execution, and eventual completion. Automatic retries, recovery, compaction, and queued work can continue after a particular turn, so a turn-end observation is not equivalent to a gate.
| Need | Useful hook or point | What it can do |
|---|---|---|
| Influence the model work for a turn | before_agent_start |
Make a routing or context decision before the agent proceeds. |
| Approve, refuse, or modify a tool call | tool_call |
Evaluate the proposed call before execution; a blocking decision can prevent the side effect. |
| Screen or transform returned tool content | tool_result |
Inspect or replace content after the tool has run. This cannot undo the tool’s external side effect. |
| Observe later outcomes | Turn-end or agent_end |
Record what happened or inform subsequent work; too late to prevent completed actions. |
The pi-jev project documents examples mapping routing, tool gating, and content screening to these decision points. Use the exact current signatures from Pi’s docs rather than treating project examples as a stable API contract.
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Keep initialization and shutdown aligned with the session
Do not open a process, socket, watcher, or timer in the extension factory: some Pi invocations load extensions without starting a session. Initialize long-lived resources in session_start, or defer initialization until the action that needs the resource. Close session-scoped resources through an idempotent shutdown handler so repeated cleanup does not create a second failure.
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Make Jev decisions conservative and inspectable
The pi-jev project describes its modules as shadow by default or disabled: they can log decisions without changing agent behavior until explicitly promoted. Its /jev command provides status, explanation, module toggles, and a kill switch. That makes shadow mode a useful calibration stage: observe classifications and latency first, then enable effects deliberately.
Separate advisory from blocking
The pi-typesafe example distinguishes advisory checks, which record a result and append qualifying feedback after execution, from blocking checks, which can refuse qualifying hazards. Advisory feedback is necessarily post-action: it cannot prevent the tool or other side effect that already occurred. Put a security control at a pre-execution hook if its purpose is prevention.
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Define failure behavior per decision
There is no universally safe fallback. If a routing judgment is unavailable, continuing with a known default model may preserve usability. If a judgment is supposed to prevent a dangerous tool call, allowing the call on timeout defeats the control; refusing it is safer but can block legitimate work. Decide explicitly how to handle timeout, authentication failure, rate limiting, transport errors, and invalid or ambiguous answers. The pi-jev-auto-mode package description presents a deterministic policy layer before semantic judgment and describes fail-closed handling when no decision can be made; this is that package’s design, not a guarantee of all Jev integrations.
- Use deterministic rules for checks that can be stated plainly, and reserve semantic judgment for cases that need it.
- Validate the response against a typed schema and the permitted decision set before applying it.
- Keep shadow mode non-interfering: log the proposed outcome, but do not accidentally mutate the call or result.
- Provide a clear kill switch and an observable reason when a decision is refused, skipped, or falls back.
Test the decision, the hook effect, and a Pi session
A helper returning the expected label does not prove the extension blocks a tool, switches a model, or replaces a result. Increase test realism in layers, asserting observable effects at each stage.
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- Unit-test decision boundaries. Cover representative inputs, threshold edges, malformed responses, and every failure branch. Assert the exact typed outcome, not only that the function completed.
- Use a fake Pi harness. Drive the registered hook and assert its returned event result and the consequential effect: model switch, tool confirmation or blocking, or tool-result replacement. Include shadow mode to prove it logs without changing behavior.
- Run a local mock judgment service. Match the Jev wire protocol and simulate success, timeout, authentication failure, rate limit, invalid JSON, and server errors. Check that each case follows the configured fallback.
- Run the real Pi CLI offline. Start Pi with the extension and controlled local mock model and judgment servers. Exercise a session end to end and verify the actual model choice, tool behavior, or screened result. Keep the run local so it is repeatable and does not depend on a live service.
The pi-jev project reports unit tests, a fake Pi harness for model switching and tool confirmation or blocking/result replacement, and offline end-to-end tests using a real Pi CLI with local mock services. These are project-reported test methods, not independent validation.
Read project fixture numbers in context
For its v0 labeled fixtures, pi-jev reports the following project-authored results. They describe those fixtures, not production workloads or a vendor benchmark.
| Measure | Project-reported result | How to interpret it |
|---|---|---|
| Router tier accuracy | 90–92% across fixture runs | Fixture accuracy; not a guarantee for a different task mix. |
| Router added latency | p50 of 288–673 ms, load-dependent | Observed median latency varied with load; no universal latency follows from it. |
| Gate dangerous-command false negatives | 0/19 | No misses in this small labeled dangerous-command fixture set. |
| Gate safe-command false positives | 5.0% (1/20) | One safe command was flagged in the cited fixture set. |
| Shield injection detection | 93.3% (14/15) | Fixture detection rate, based on 15 labeled examples. |
The project says net model cost change, real-session gate cache hit rate, and prune token savings were not measured. Do not infer savings or production reliability from the fixture results.
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Review security and package trust before enabling effects
Pi’s package gallery warns that packages can execute code and influence agent behavior. Review the extension source and its network behavior before installation, especially when it can inspect prompts, tool calls, or returned content. The Pi package gallery is the relevant place to check package identity and current listing details; a gallery entry is not itself a security audit.
Begin with the least consequential mode, inspect logs for unexpected classifications, then enable a particular module only after its failure paths and false-positive impact are acceptable. Keep externally transmitted data minimal and provide operators with a way to disable the behavior quickly.
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