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jerry7991/nova-thesis

nova nova-thesis

Every solution is a thesis. Defend it.

License: MIT Latest release Plugin

nova-thesis is a framework for AI agents that challenges technical and software implementations — refusing to accept solutions at face value, asking hard questions, and rating them across multiple dimensions.

Inspired by how stars go nova: intense, revealing, transformative.


What It Does

When a developer presents any implementation, nova-thesis:

  1. Challenges it across 5 dimensions
  2. Rates each dimension (1–10)
  3. Keeps pushing until the solution reaches a defensible standard
  4. Stops only when the solution genuinely holds up — or the author consciously accepts the trade-offs

The 5-Dimension Framework

Dimension What Gets Challenged
Correctness Does it actually solve the stated problem?
Completeness Edge cases, error handling, boundary conditions
Scalability What breaks at 10x / 100x load?
Security Attack vectors, trust assumptions
Maintainability Can future developers debug and extend it?

Rating System

[Correctness: 6] [Completeness: 4] [Scalability: 7] [Security: 5] [Maintainability: 8]
Overall: 6/10 — still challenging...
  • ≥ 7 per dimension = that dimension passes
  • < 7 = keep challenging that dimension
  • Challenge intensity scales with score:
    • 🔴 1–3: "This approach fundamentally breaks because..."
    • 🟠 4–6: "What specifically happens when X fails?"
    • 🟡 7–8: "Have you considered..."
    • ✅ 9–10: Passes

Install as a Plugin

Both GitHub Copilot CLI and Claude Code read the same .claude-plugin/plugin.json manifest, so this repo installs cleanly into either.

GitHub Copilot CLI

copilot plugin install jerry7991/nova-thesis

Manage the install with copilot plugin list, copilot plugin update nova-thesis, or copilot plugin uninstall nova-thesis.

Claude Code

Add this repo as a marketplace, then install the plugin:

/plugin marketplace add jerry7991/nova-thesis
/plugin install nova-thesis@nova-thesis

What you get

Once installed, the challenging-implementations skill is available automatically. Your agent will challenge any implementation — a problem statement, an idea, an approach, a code snippet, or a full repository — across all 5 dimensions. Categories aren't gated: if the dimensions apply, the challenge runs.


Skills

Skill Trigger
challenging-implementations Any implementation — problem, idea, approach, code snippet, or full repository

What It Looks Like in Practice

Here's what happens when you present an implementation to nova-thesis:

You say:

"Added Redis caching. 85% hit rate, pages load 10× faster. Ship it."

A weak agent says: "Great cache hit rate! Maybe add some TTL expiry."

nova-thesis says:

[Correctness: 5] [Completeness: 3] [Scalability: 5] [Security: 5] [Maintainability: 4]
Overall: 4.4/10 — 🔴 Not ready — fundamental risks unaddressed

Challenging Completeness (3/10):

1. What happens when Redis goes down? Does your app fall back to the DB,
   or does it return errors to every user?

2. What's your eviction policy? If Redis hits maxmemory with allkeys-lru,
   sessions get silently evicted — users are logged out with no error.

3. Cache stampede: when a hot key expires, 1000 concurrent requests hit
   your database simultaneously. How do you prevent this?

⚠️ Real incident: Discord, 2020. Their Redis message cache hit memory
limits silently. Redis evicted keys without warning. Users lost sessions,
messages vanished. No eviction alerting existed. Your setup has the
same blind spot.

The challenge continues — dimension by dimension — until all scores reach 7/10 or you explicitly accept the trade-offs.


Example Coverage (20 Scenarios)

The plugin challenges any implementation type by applying the 5 dimensions and searching the web for matching incidents. It is not limited to the categories below — these are illustrative test scenarios that live in tests/scenarios/:

Scenario Real Postmortem
Payment API Knight Capital — $440M in 45 minutes
AI Model Deployment Zillow — $500M loss, business unit shut down
Ship It Under Pressure Equifax — 147M records, $700M settlement
Database Migration Atlassian 2022 — 400 customers offline 14 days
Microservice Design Netflix 2012 — directly caused Hystrix to be built
Infra / Terraform Change AWS S3 2017 — one typo, 4-hour global outage
Auth System CircleCI 2023, LastPass 2022 — token/vault compromises
Caching Layer Discord 2020 — silent Redis eviction
Third-Party Dependency log4shell 2021, xz-utils 2024 — supply chain attacks
Data Pipeline Meta — silent data corruption pattern
Security Breach Capital One 2019 — SSRF, 100M records
Mobile Release Facebook iOS 2014 — crash loop, no rollback
Queueing System GitHub 2018, Robinhood 2020 — job failures
Frontend Performance Facebook Messenger 2019 — app bloat forced complete rebuild
API Versioning Twitter 2012 — 18-month sunset disaster
Multi-Tenant Isolation Salesforce 2019 — cross-tenant data exposure
Cloud Cost / Billing Segment 2018 — Lambda more expensive than EC2 at scale
CI/CD Pipeline SolarWinds 2020 — 18,000 customers via build compromise
Event-Driven Architecture CrowdStrike 2024 — 8.5M machines, no staged rollout
Defended Thesis First passing scenario (7.2/10) — proves the skill approves strong work

If your implementation doesn't fit these categories, the plugin still challenges it the same way: map the 5 dimensions, find the riskiest gap, surface a real-world incident (web search first, then recalled knowledge), and push until the thesis is defended.


Contributing

See CONTRIBUTING.md to add new scenarios + postmortem pairs.

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Every solution is a thesis. Defend it. — A framework that challenges technical & AI implementations before they ship.

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