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tldr-pages
tldr
Markdown2014–2026
tldr-pages / tldr

tldr

Collaborative cheatsheets for console commands 📚.

78Distinct people
83Mentions
3Explicit recommenders
64.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Collaborative cheatsheets for console commands 📚.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

I love tldr for this https://github.com/tldr-pages/tldr

lrobinovitch used a recommendation phrase. 3 indexed comments match. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year83 dated mentions

Observed mentions: 2014-01-26 09:30:53 UTC to 2026-10-26 16:25:09 UTC.

0510152014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 6 mentions; 1 submissions, 5 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 5 mentions; 3 submissions, 2 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 7 mentions; 0 submissions, 7 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 9 mentions; 4 submissions, 5 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 11 mentions; 0 submissions, 11 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 13 mentions; 2 submissions, 11 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC211
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC413
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC615
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC532
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC707
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC945
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC11011
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC716
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC13211
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC808
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC303
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC514
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC312

What Hacker News says

83 sources
Before LLMs there existed quite a few tools to try to help with understanding CLI options; off the top of my head there are https://github.com/tldr-pages/tldr and explainshell.com LLMs are both more general and more useful than those tools. They're more flexible and composable, and can replace those tools with a small wrapper script. Part of the reason why the LLMs can do that though is because it has those other tools as datasets to train off of.
In AI Coding and the Peanut Butter and Jelly Problem

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