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ai-agents-for-science/scope-interview-agent

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App README

📋 Scope Interview Agent

A strict, structured requirements interviewer: it extracts a complete Scope Requirements Document from engineers, scientists, and project managers before any design or implementation begins — one focused question at a time, across nine mandatory interview steps.

Artifacts-driven: the agent's instructions are NOT hardcoded. They are loaded at startup from ./artifact/agents.md — the CARE v2 artifact: the scope-interview skill from NASA-IMPACT/akd-plugins (plugins/scope-interview/skills/scope-interview/SKILL.md), bundled verbatim. A web-chat session addendum adapts its Claude-Code-specific parts (codebase exploration, file saving) to this UI. If reference files ever ship alongside the skill, they are exposed through a read_reference tool automatically.

Guardrailed (pydantic-ai v2 harness): every turn is checked by the NASA-IMPACT/akd-guardrails service, attached as InputGuard / OutputGuard capabilities on the agent — gliguard (GLiNER) screens each user prompt before the model is invoked (hard block, zero tokens), and risk_agent (LLM judge) reviews the final answer with the interview's recent turns as grounding context before it renders. No guard logic lives in this app; it only relays verdicts. Blocked turns show ⛔ Blocked by AKD input/output guardrails: <risks>, and blocked answers never enter the conversation memory. If the guardrails service itself is unreachable, checks fail open (logged).

What it does

—Guides you through 9 interview steps (problem understanding, stakeholder mapping, scope boundaries, assumptions, requirements, entities, workflows, risks)
—Live progress bar tracks the interview step
—Streams a collapsible reasoning trace per reply
—Produces a Scope Requirements Document at the end, downloadable as .md
—Strictly scoped: extracts requirements only — no design, no architecture, no code
—Model + reasoning-effort selectors (bring-your-own OpenAI key)

Run locally

bash

cd scope-interview-agent
pip install -r requirements.txt
python app.py

Configuration

Variable	Required	Purpose
OpenAI API key	yes	Entered by each visitor in the UI (bring-your-own-key).
`AKD_GUARDRAILS_URL`	no	AKD guardrails service base URL (default: the dev ALB).
`ARTIFACT_DIR`	no	Artifact folder override (default `./artifact`).
`AGENT_MODEL`	no	Default model id (default `gpt-5.2`).

No server-side secrets are required. Each visitor supplies their own OpenAI key at runtime.