npm package: @lnittman/pi-interview
Description: Multiple-choice + notes interview for pi — ask-deep style structured prompting after every agent turn
Author: Luke Nittmann
Latest version: 0.28.4
Deprecated: Package no longer supported. Contact Support at https://www.npmjs.com/support for more info.

# @lnittman/pi-interview

High-trust interview extension for [pi](https://github.com/mariozechner/pi-coding-agent).

`pi-interview` turns the next-step decision after an agent turn into a grounded interview:

- multi-select questions with notes
- cold-start support (`Ctrl+I` / `/interview ask` before any assistant turn)
- rich grounding from files, diagnostics, trajectory, project state, and `~/.agents/**`
- provider-first settings with separate `interviewModel` and `handoffModel` selection from the same interview fleet
- curated context-richness profiles (`focused`, `balanced`, `rich`) instead of raw context-engineering knobs
- workflow-aware prompting that treats debrief as a phase-transition tool instead of a generic default
- viewport-aware interview rendering for long option descriptions and grounding, with grounding hidden until you reveal it in the interview UI
- composed follow-up prompts that send a synthesized handoff brief plus an exact interview appendix into the next agent turn

## Commands

- `/interview ask` — trigger manually
- `/interview settings` — choose `interviewModel`, `handoffModel`, allowed model fleet, context profile, capability-aware thinking level, and trigger mode
- `/interview status` — show config, usage status, and latest interview/handoff runtime details
- `/interview audit` — inspect the current context packet
- `/interview trace` — toggle trace-rich context auditing
- `Ctrl+I` — manual interview shortcut

## Development

```bash
cd ~/Developer/packages/pi/pi-interview
pnpm install
pnpm build
pnpm test
pnpm typecheck
```

## Subjective quality evals

This repo includes a Braintrust-based subjective eval stack in addition to deterministic regression tests.

Commands:

```bash
pnpm telemetry:evals:list
pnpm telemetry:evals:quality
pnpm telemetry:evals:pairwise
pnpm telemetry:evals:workflow
pnpm telemetry:evals:portfolio
pnpm telemetry:evals:handoff
pnpm telemetry:evals:handoff:variants
pnpm telemetry:dataset:seed
```

Use Doppler for secrets:

```bash
doppler run -- pnpm telemetry:evals:quality
doppler run -- pnpm telemetry:evals:pairwise
doppler run -- pnpm telemetry:evals:workflow
doppler run -- pnpm telemetry:evals:portfolio
doppler run -- pnpm telemetry:evals:handoff
doppler run -- pnpm telemetry:evals:handoff:variants
doppler run -- pnpm telemetry:dataset:seed
```

Example portfolio sweep, including `gpt-5.4` as a real fallback generator candidate:

```bash
doppler run -- env PI_INTERVIEW_EVAL_MODELS=zai/glm-5.1,minimax/MiniMax-M2.7-highspeed,openai/gpt-5.4 pnpm telemetry:evals:portfolio
```

Example replay-backed handoff variants sweep with explicit `interviewModel × handoffModel × receiverModel` matrices:

```bash
doppler run -- env PI_INTERVIEW_HANDOFF_SOURCE=replay PI_INTERVIEW_EVAL_INTERVIEW_MODELS=zai/glm-5.1,minimax/MiniMax-M2.7-highspeed PI_INTERVIEW_EVAL_HANDOFF_MODELS=zai/glm-5.1,minimax/MiniMax-M2.7-highspeed PI_INTERVIEW_EVAL_RECEIVER_MODELS=zai/glm-5.1 PI_INTERVIEW_HANDOFF_VARIANTS=legacy,static,appendix,agentic pnpm telemetry:evals:handoff:variants
```

Full eval playbook:

- `docs/evals.md`

## License

MIT