Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

Badge that shows how well your codebase fits in an LLM's context window

Details

External ID
47181471
Source
HN
Company
—
Product
Badge that shows how well your codebase fits in an LLM's context window
Website domain
github.com
Launched
Feb. 27, 2026
Cohort
—
Upvotes
88
Upvotes percentile
0.8800539083557951
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Small codebases were always a good thing. With coding agents, there's now a huge advantage to having a codebase small enough that an agent can hold the full thing in context.Repo Tokens is a GitHub Action that counts your codebase's size in tokens (using tiktoken) and updates a badge in your README. The badge color reflects what percentage of an LLM's context window the codebase fills: green for under 30%, yellow for 50-70%, red for 70%+. Context window size is configurable and defaults to 200k (size of Claude models).It's a composite action. Installs tiktoken, runs ~60 lines of inline Python, takes about 10 seconds. The action updates the README but doesn't commit, so your workflow controls the git strategy.The idea is to make token size a visible metric, like bundle size badges for JS libraries. Hopefully a small nudge to keep codebases lean and agent-friendly.GitHub: https://github.com/qwibitai/nanoclaw/tree/main/repo-tokens

Enrichment

Theme
git and repository workflow tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
measure codebase fit in llm context windows
Manually corrected
False

Could you build this?

Yes This is a simple GitHub Action script that reads repository files, runs the public tiktoken library to count tokens, and updates a Shields.io or custom SVG badge.

Discussion

20 comments analyzed.

Competitors mentioned: repomix for source bundling, RAG with AST transformation, uithub.com (open source alternative)

Concerns raised: Token limits hit quickly with inefficient LLM summarization, Metric doesn't reflect practical usage (not all files needed simultaneously), Rewards dynamic languages over typed languages, Penalizes comments and descriptive naming, Entire codebase context may not be necessary or useful

Feature requests: Strip comments from read file tools to reduce tokens, Measure token count for only recently-edited files, Scope AI access to relevant domain areas only, not entire codebase, Support modular design with interface/implementation separation for agents, Integrate with documentation instead of raw codebase

Competitors

Other products that read as similar to this one — 60 launches clear the similarity bar, closest 8 shown.

Attention rank: #8 of 61 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 113 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a dev tools tool for Sales yet.