crate-ci/typos

Source code spell checker

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Summary Information

Updated 3 minutes ago
Added to GitGenius on September 16th, 2026
Created on April 16th, 2019
Open Issues & Pull Requests: 150 (+0)
GitHub issues: Enabled
Number of forks: 186
Total Stargazers: 4,145 (+0)
Total Subscribers: 7 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.3 hours
Mean response time: 10.9 days
90th percentile: 2.6 days
Tracked items: 301

Most active contributors

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How this project is maintained

Practically every issue opened in the past year has drawn a reply. 92% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 74% of issues opened in the past year have been closed, leaving a working backlog. Three people close 82% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 126
New in 7 days: 0
Closed in 7 days: 2
Avg open age: 892 days
Stale 30+ days: 1
Stale 90+ days: 1

Recent activity

Opened in 7 days: 0
Closed in 7 days: 2
Comments in 7 days: 2
Events in 7 days: 329

Top labels

  • S-triage (110)
  • A-dict (29)
  • C-enhancement (15)
  • A-exclude (7)
  • C-bug (7)
  • A-gh-action (3)
  • A-precommit (3)
  • A-token (3)

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Detailed Description

typos is a source code spell checker that finds and corrects spelling errors in code and documentation.

The tool addresses the problem of typos slipping into codebases by scanning source files for misspelled words. It works by maintaining a dictionary of correct spellings and flagging deviations, then offering correction suggestions. The spell checker is designed specifically for code rather than natural language, meaning it understands programming conventions and avoids false positives on identifiers, variable names, and technical terms that would trip up a general-purpose spell checker.

Developers should choose typos if they want automated spelling verification integrated into their development workflow or CI/CD pipeline. It suits projects of any size that care about code quality and documentation accuracy. The tool is particularly valuable for teams that want to catch spelling mistakes before they reach version control, and it can be run locally during development or as a gate in continuous integration systems.

The project shows consistent maintenance with regular updates addressing bug fixes and expanding dictionary coverage. Development activity demonstrates responsiveness to user-reported issues and a willingness to refine the tool's behavior based on feedback. The maintainers actively work to reduce false positives by improving how the spell checker handles code-specific patterns and technical terminology.