DEV Community: 闫品权

35 free developer tools that run entirely in your browser — no signup, no uploads

闫品权 — Sat, 10 Oct 2026 06:41:53 +0000

Two things always bothered me about the usual "paste your JSON here" websites: half of them quietly upload your data to a server, and the other half drown you in ads. When you are pasting an access token into a JWT decoder, "where does this data actually go?" is not a paranoid question.

So we built a collection of developer tools where everything runs in your browser. No account, no uploads, no server round-trips — the parsing happens in JavaScript on your own machine. Here are the ten I reach for most often.

1. JSON Formatter

https://hysenlabs.com/tools/json-formatter

Formats, validates and minifies JSON. The error message points at the exact character that broke your config, which is the difference between 30 seconds and five minutes of staring at a bracket.

2. JWT Decoder

https://hysenlabs.com/tools/jwt-decoder

Decodes the header and payload instantly and flags expiration. Handy when debugging auth flows — and since the token never leaves your machine, it stays safe to use with real tokens.

3. Cron Parser

https://hysenlabs.com/tools/cron-parser

Explains any cron expression in plain English ("at 03:00, every 5 days") and shows the next scheduled runs. I no longer pretend to remember what */15 2-6 * * 1-5 means.

4. Regex Tester

https://hysenlabs.com/tools/regex-tester

Live highlighting of matches as you type, including capture groups. Test patterns against your real sample data locally, not through someone else's API rate limit.

5. SQL Formatter

https://hysenlabs.com/tools/sql-formatter

Turns the 200-character one-liner from your ORM logs into something a human can read during code review. Supports multiple SQL dialects.

6. UUID Generator

https://hysenlabs.com/tools/uuid-generator

Bulk v4 UUIDs in one click, with a "copy all" button. Works offline.

7. Hash Generator

https://hysenlabs.com/tools/hash-generator

MD5, SHA-1, SHA-256 and SHA-512 from text or a file. Useful for checksums and cache keys without dropping into a shell.

8. Base64

https://hysenlabs.com/tools/base64

Encodes and decodes text and files, including the URL-safe variant that trips people up constantly when working with JWTs.

9. Diff Checker

https://hysenlabs.com/tools/diff-checker

Side-by-side text diff with changed lines highlighted. Paste two versions of a config file and see exactly what moved.

10. Timestamp Converter

https://hysenlabs.com/tools/timestamp-converter

Unix timestamps to human-readable time and back, timezone aware. Debugging a 1700000000 in a log line? Paste, done.

The rest of the set

The full collection currently has 35 tools — URL parser, user-agent parser, HTML entity encoder, color converter, CSV to Markdown, AES encryption, HMAC generator and more. All free, all client-side:

hysenlabs.com/tools

One more thing

The same site publishes a weekly GitHub star-growth ranking with an open methodology and a downloadable dataset, if you like tracking which open-source projects are genuinely trending rather than just loud on social media:

https://hysenlabs.com/data/star-growth

Everything runs client-side, so paste away — your data stays in your browser tab. If you have ideas for tools worth adding, the feedback link on the site works and we actually read it.

Nine weeks of GitHub star growth: 64% of weekly winners appeared only once

闫品权 — Mon, 28 Sep 2026 09:11:38 +0000

For the last nine weeks I have been taking daily snapshots of GitHub stars for roughly 19,000 open-source projects. Every Monday I publish a top 10 based on star growth since the previous week. Each week gets a fixed page that is never edited afterwards.

I started the project because weekly trending lists are easy to read and hard to trust. A repository can get a burst of attention from a release, a conference talk, or one popular post. I wanted to know how often that burst lasted.

The answer so far: not very often.

The numbers

There are nine complete weeks in the archive, from 2026-07-27 through 2026-09-21. That gives us 90 slots.

47 distinct projects filled those slots.
30 projects, or 64%, appeared exactly once.
The average overlap between one week and the next was 4.9 out of 10.
The overlap ranged from 2 to 6.

The weekly carryover looks like this:

Week starting	Projects still on the list
2026-08-03	6
2026-08-10	5
2026-08-17	5
2026-08-24	5
2026-08-31	6
2026-09-07	6
2026-09-14	2
2026-09-21	4

Most weeks replaced about half the list. The week of 2026-09-14 was more extreme: only two projects stayed from the week before.

Long streaks are rare

Three projects lasted seven weeks in a row: mattpocock/skills, stablyai/orca, and DietrichGebert/ponytail.

All three dropped out in the same week, 2026-09-14. That was also the week with the highest turnover in the sample. The result looked like a clean end to the only real streak in the data.

It was not. stablyai/orca returned to the top 10 the following week.

That single reversal is useful. It shows why one week in a trending list is a weak signal. It also shows why dropping out for one week does not prove that interest has disappeared. With nine weeks of data, I can describe what happened in this period. I cannot use it to predict what a repository will do next year.

How the ranking is calculated

Each week compares two daily snapshots: the one nearest the Monday boundary and the one nearest the Sunday boundary. Both snapshots must fall within 36 hours of the boundary. If either one is missing, the repository is dropped for that week rather than estimated.

Archived, mirrored, and unlisted repositories are excluded. A week only enters the archive when it has ten projects. The first week in the source data had seven, so it is not part of the nine complete weeks.

The project list leans toward AI and developer tooling. It is not a random sample of GitHub.

Stars are also noisy. A popular post can move the number by thousands in a day, and not every star represents a user who will keep using the project. The ranking measures attention, not maintenance, code quality, or long-term adoption.

What I look at instead

A weekly ranking is useful for finding projects I have not seen before. It is not a good reason to adopt one.

For that decision I look at the last commit, recent releases, open issues, and whether the repository has been archived. The license matters too. A permissive license, a copyleft license, and a source-available license can lead to very different outcomes for a product.

The weekly list is a starting point. The repository itself has to answer the rest.

Data and method

The archive is here: https://hysenlabs.com/en/weekly

The latest complete week is here: https://hysenlabs.com/en/weekly/2026-09-21

There is also a rolling 30-day growth table with a CSV download: https://hysenlabs.com/en/data/star-growth

If you find an error in the method, send me the details. I would rather correct the dataset than defend a bad number.