Key Findings

Discovered Topics

๐Ÿ”จ
Project Structure
Build commands, package managers, and dependency setup
issue
0.3743
project
0.3513
build
0.3371
python
0.3182
update
0.3174
check
0.3069
work
0.3061
command
0.3018
module
0.2988
package
0.2983

This topic represents a cluster of related terms discovered through topic modeling analysis. The word weights indicate how strongly each term is associated with this theme across the analyzed repositories.

๐Ÿงช
Writing & Training
Test runners, linting, and validation workflows
writing
0.7968
training
0.6075
nextjs
0.5928
read
0.5885
breaking
0.5344
know
0.513
apis
0.503
relevant
0.4303
guide
0.4178
exact
0.3902

This topic represents a cluster of related terms discovered through topic modeling analysis. The word weights indicate how strongly each term is associated with this theme across the analyzed repositories.

โœ๏ธ
Frontend Development
Code style, formatting conventions, and naming rules
npm
0.9068
bun
0.4412
pnpm
0.4165
component
0.3748
build
0.356
typescript
0.3067
frontend
0.2547
react
0.2419
api
0.2273
app
0.2095

Frontend-focused CLAUDE.md files are among the most detailed. The prevalence of "npm," "typescript," and "react" reflects the dominance of the React/TypeScript ecosystem in projects using Claude Code. These files typically specify component patterns, state management, and build tooling.

๐Ÿ›๏ธ
Tool & Model
Project architecture, modules, and directory structure
tool
0.9136
model
0.3781
mcp
0.244
prompt
0.2388
llm
0.2282
python
0.2137
return
0.2059
description
0.1967
import
0.189
data
0.1763

This topic represents a cluster of related terms discovered through topic modeling analysis. The word weights indicate how strongly each term is associated with this theme across the analyzed repositories.

โ›”
Skill & Memory
Constraints, prohibitions, and agent guardrails
skill
1.4775
memory
0.2347
pressure
0.1825
memorymd
0.1625
markdown
0.1547
dont
0.1485
doc
0.1463
session
0.1399
user
0.1383
scenario
0.1286

This topic represents a cluster of related terms discovered through topic modeling analysis. The word weights indicate how strongly each term is associated with this theme across the analyzed repositories.