REPOGEO REPORT · LITE

deeplethe/forkd

Default branch main · commit 03d55c29 · scanned 7/1/2026, 4:33:18 PM

GitHub: 2,692 stars · 208 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface deeplethe/forkd, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Clarify forkd's purpose immediately in the README

Why:

CURRENT

A microVM sandbox runtime for **AI agent fan-out**. Children fork from a warmed parent snapshot, inheriting its address space copy-on-write instead of cold-booting their own kernel.

COPY-PASTE FIX

# forkd: Fork() for AI agent microVMs.
Spawn 100 children in ~100ms from a warm parent; BRANCH a live VM in ~150ms. KVM-isolated, snapshot CoW.
(Note: This project is a microVM runtime, not a tool for managing GitHub repositories.)

mediumreadme#2

Add a 'Comparison' section to the README

Why:

COPY-PASTE FIX

## Comparison to Firecracker, Kata Containers, and other MicroVMs
While forkd is built on Firecracker, it provides a specialized layer for rapid, copy-on-write forking of warmed microVMs, specifically optimized for AI agent fan-out and parallel execution. Unlike general-purpose microVM solutions, forkd focuses on the unique challenges of quickly spawning many isolated, pre-initialized environments from a shared parent state, offering significantly faster spin-up times than cold-booting individual VMs or using container orchestration for this specific use case.

lowhomepage#3
Add homepage URL to repository metadata
Why:
COPY-PASTE FIX
```
https://github.com/deeplethe/forkd
```

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface deeplethe/forkd

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Docker Swarm

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Docker Swarm · recommended 1×
Kubernetes (K8s) · recommended 1×
Google Kubernetes Engine (GKE) · recommended 1×
Amazon Elastic Kubernetes Service (EKS) · recommended 1×
Azure Kubernetes Service (AKS) · recommended 1×

CATEGORY QUERY
How to quickly spin up many isolated AI agent environments for parallel execution?
you: not recommended
AI recommended (in order):
1. Docker Swarm
2. Kubernetes (K8s)
3. Google Kubernetes Engine (GKE)
4. Amazon Elastic Kubernetes Service (EKS)
5. Azure Kubernetes Service (AKS)
6. Ray
7. AWS Batch
8. Google Cloud Batch
9. Azure Batch
10. Apache Mesos
11. Marathon
12. Aurora
13. Nomad
AI recommended 13 alternatives but never named deeplethe/forkd. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to efficiently fork hundreds of isolated microVMs from a warm parent for AI agents?
you: not recommended
AI recommended (in order):
1. Firecracker (firecracker-microvm/firecracker)
2. Kata Containers (kata-containers/kata-containers)
3. Cloud Hypervisor (cloud-hypervisor/cloud-hypervisor)
4. QEMU/KVM
5. gVisor (google/gvisor)
6. CrosVM (chromium/crosvm)
AI recommended 6 alternatives but never named deeplethe/forkd. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of deeplethe/forkd?
pass
AI named deeplethe/forkd explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts deeplethe/forkd in production, what risks or prerequisites should they evaluate first?
pass
AI named deeplethe/forkd explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo deeplethe/forkd solve, and who is the primary audience?
pass
AI named deeplethe/forkd explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of deeplethe/forkd. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/deeplethe/forkd.svg)](https://repogeo.com/en/r/deeplethe/forkd)

HTML

<a href="https://repogeo.com/en/r/deeplethe/forkd"><img src="https://repogeo.com/badge/deeplethe/forkd.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

deeplethe/forkd — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite