REPOGEO REPORT · LITE

mthenw/awesome-layers

Default branch master · commit 7deb0685 · scanned 5/14/2026, 10:13:54 PM

GitHub: 2,259 stars · 185 forks

AI VISIBILITY SCORE

33 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 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 mthenw/awesome-layers, 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

Reposition README introduction to clarify repo's purpose as a list

Why:

CURRENT

**A curated list of awesome AWS Lambda Layers**

## What are Lambda Layers?

COPY-PASTE FIX

**A curated list of awesome AWS Lambda Layers**

This repository helps developers quickly find and leverage pre-built custom runtimes, utilities, and monitoring solutions as AWS Lambda Layers, saving development time and promoting reuse.

## What are Lambda Layers?

mediumtopics#2

Add 'awesome-list' to topics

Why:

CURRENT

awesome, aws, aws-lambda, cloud, serverless, serverless-application-model, serverless-framework, serverless-functions

COPY-PASTE FIX

awesome, aws, aws-lambda, cloud, serverless, serverless-application-model, serverless-framework, serverless-functions, awesome-list

lowreadme#3

Add introductory sentences to 'How to create/use' and 'How to share' sections

Why:

CURRENT

## How to create and use Lambda Layers?
* with Serverless Framework
* with SAM
* with AWS Console
* with AWS CLI (tutorial),
* with Stackery

## How to share Lambda Layers publicly?
* Tutorial with CLI examples

COPY-PASTE FIX

## How to create and use Lambda Layers?
These resources provide context and methods for integrating Lambda Layers into your projects, complementing the pre-built layers listed below.
* with Serverless Framework
* with SAM
* with AWS Console
* with AWS CLI (tutorial),
* with Stackery

## How to share Lambda Layers publicly?
For those interested in contributing or publishing their own layers, this section offers guidance.
* Tutorial with CLI examples

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 mthenw/awesome-layers

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Lambda Layers

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Lambda Layers · recommended 1×
serverless/serverless · recommended 1×
AWS SAM · recommended 1×
AWS CodeArtifact · recommended 1×
GitHub Packages · recommended 1×

CATEGORY QUERY
How to efficiently share common dependencies and code across multiple serverless functions?
you: not recommended
AI recommended (in order):
1. Lambda Layers
2. Serverless Framework (serverless/serverless)
3. AWS SAM
4. AWS CodeArtifact
5. GitHub Packages
6. Nexus
7. Artifactory
8. devpi (devpi/devpi)
9. AWS Lambda
10. Google Cloud Run
11. Azure Container Apps
12. S3 Bucket
13. Git Submodules
14. Git Subtrees
AI recommended 14 alternatives but never named mthenw/awesome-layers. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where can I find pre-built custom runtimes or monitoring solutions for serverless functions?
you: not recommended
AI recommended (in order):
1. Datadog
2. New Relic
3. Thundra
4. Lumigo
5. AWS X-Ray
6. Serverless Framework
7. CloudWatch (AWS)
8. Azure Monitor (Azure)
9. Google Cloud Monitoring (GCP)
AI recommended 9 alternatives but never named mthenw/awesome-layers. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 mthenw/awesome-layers?
pass
AI named mthenw/awesome-layers explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts mthenw/awesome-layers in production, what risks or prerequisites should they evaluate first?
pass
AI named mthenw/awesome-layers 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 mthenw/awesome-layers solve, and who is the primary audience?
pass
AI did not name mthenw/awesome-layers — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/mthenw/awesome-layers.svg)](https://repogeo.com/en/r/mthenw/awesome-layers)

HTML

<a href="https://repogeo.com/en/r/mthenw/awesome-layers"><img src="https://repogeo.com/badge/mthenw/awesome-layers.svg" alt="RepoGEO" /></a>

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