AgentOps

An enterprise AI agent governance control tower.

▶ Live demo: agentops-fpl.vercel.app · Highlights & decisions: docs/highlights.md

Companies are deploying AI agents everywhere — ticket triage, release notes, support summaries, policy Q&A — and leadership has no single place to answer: which agents exist, who owns them, what data they touch, are they any good, and should they ship? AgentOps inventories every agent, scores its risk, surfaces its evaluation metrics, and gives each one a launch-readiness recommendation: Launch, Conditional, Needs Review, or Do Not Launch.

Part of Fischer Product Lab — secure AI systems for trust, risk, and enterprise execution.

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Security & data posture (read this first)

This is a public, read-only demonstration built entirely on synthetic data.

• Synthetic data only. Every agent, owner, metric, and audit entry is invented. No real employer, customer, or personal data is present anywhere in this repository or the deployed demo.
• Read-only. There are no forms, no mutations, no public write endpoints, and no admin surface. The demo only displays.
• No AI calls. The readiness score is deterministic — plain rules and math — which is what makes it explainable and auditable.
• No secrets in the browser. No API keys or sensitive values exist in client-side code; V1 requires no environment variables at all.

See SECURITY.md for the full posture and docs/threat-model.md for the STRIDE analysis.

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What's inside

Four screens:

Route	Screen	Purpose
/	Executive Dashboard	Portfolio at a glance: totals, counts by readiness, hours saved, a "needs attention" list, and two charts.
/registry	Agent Registry	A sortable, risk-aware table of every agent.
/registry/[id]	Agent Detail	One agent in full: purpose, data/tools, evaluation metrics, the readiness scorecard with its 7-criteria breakdown and reasons, failure modes, and an audit log. Agents with a shipped counterpart link out to its post-launch performance in ProductPulse.
/about	About this demo	Why AgentOps exists, how the readiness engine works, the security posture, and the rest of the Fischer Product Lab suite.

The readiness engine (the centerpiece)

lib/readiness.ts is a pure, deterministic function. Given an agent's seven rubric scores (0–4 each), it:

1. Computes a weighted score normalized to 0–100.
2. Maps it to a band (80+ Launch, 60–79 Conditional, 40–59 Needs Review, <40 Do Not Launch).
3. Applies two hard safety gates — a high average can never override a critical safety floor:
   • If Data Safety or Tool Permission Risk ≤ 1, the verdict is capped at Needs Review.
   • If both ≤ 1, the verdict is forced to Do Not Launch.

Verdicts are always computed, never stored, so every status is a reproducible, auditable function of the rubric. The logic is covered by tests in lib/readiness.test.ts.

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Tech stack

• Next.js 16 (App Router) + React 19
• TypeScript in strict mode
• Tailwind CSS v4
• Recharts for data visuals
• Zod for schema validation
• Lucide icons
• Node's built-in test runner (node --test)

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Getting started

Prerequisites: Node.js LTS and pnpm.

# Install dependencies
pnpm install

# Run the dev server (http://localhost:3000)
pnpm dev

# Type-check + production build
pnpm build

# Run the readiness engine tests
pnpm test

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Project structure

agentops/
├── app/
│   ├── page.tsx                 # Executive dashboard (/)
│   ├── registry/
│   │   ├── page.tsx             # Agent registry (/registry)
│   │   └── [id]/page.tsx        # Agent detail (/registry/[id])
│   ├── about/page.tsx           # About this demo (/about)
│   ├── layout.tsx               # Root layout + app shell
│   └── globals.css              # Design system (Tailwind v4 theme)
├── components/
│   ├── layout/                  # Sidebar, top bar, app shell
│   ├── dashboard/               # Status donut, hours-by-team chart
│   ├── agent/                   # Score ring, rubric breakdown, eval panel
│   ├── registry/                # Sortable registry table
│   └── status-badge.tsx         # Shared readiness badge + status colors
├── data/
│   └── agents.ts                # 8 synthetic agents (typed)
├── lib/
│   ├── types.ts                 # Domain types
│   ├── readiness.ts             # Deterministic readiness engine
│   └── readiness.test.ts        # Tests for the engine + safety gates
└── docs/
    ├── agentops-prd.md          # Product requirements
    ├── highlights.md            # Project highlights
    ├── threat-model.md          # STRIDE analysis
    └── BUILD_LOG.md             # Build narrative & key decisions

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License

This project is a portfolio demonstration. © Trevor Fischer / Fischer Product Lab.