lint
Run golangci-lint and static analysis on Go code. Use before pushing or to check code quality.
Best use case
lint is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Run golangci-lint and static analysis on Go code. Use before pushing or to check code quality.
Teams using lint should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/lint/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How lint Compares
| Feature / Agent | lint | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Run golangci-lint and static analysis on Go code. Use before pushing or to check code quality.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Go Linting Run golangci-lint to check code quality and catch issues before CI. ## Usage - `/lint` - Lint all packages - `/lint ./internal/repo/...` - Lint a specific package ## Steps 1. **Run golangci-lint** ```bash golangci-lint run $ARGUMENTS 2>&1 ``` If no arguments provided, run on all packages: ```bash golangci-lint run ./... 2>&1 ``` 3. **If golangci-lint is not installed**, install it: ```bash go install github.com/golangci/golangci-lint/cmd/golangci-lint@latest ``` Then re-run step 2. 4. **Parse and report findings** Group issues by severity and file: ``` ## Lint Results ### Errors - [list of errors with file:line references] ### Warnings - [list of warnings with file:line references] ### Summary - Total issues: N - Files affected: N ``` 5. **Offer to fix auto-fixable issues** If issues are auto-fixable, offer to run: ```bash golangci-lint run --fix $ARGUMENTS 2>&1 ``` ## Configuration The project uses `.golangci.yml` in the repo root. Read this file to understand which linters are enabled/disabled before interpreting results. Current exclusions: - `internal/codesearch/` - excluded from linting and formatting (forked upstream code) ## CI Alignment The CI pipeline runs `golangci-lint`, `go vet ./...`, and `gosec` (see `/security-scan` skill). Running `/lint` locally before pushing catches most CI failures.
Related Skills
test
Run Go unit tests. Use after code changes to verify correctness.
security-scan
Run gosec and govulncheck to find security vulnerabilities. Use before releases or after dependency changes.
reindex
Trigger reindexing of a specific WordPress extension. Use to rebuild the search index for a plugin, theme, or core version.
race-check
Run Go race detector to find data races in concurrent code. Use after any change to mutexes, goroutines, or channels.
profile
Run CPU and memory profiling with pprof to identify performance hotspots. Use when investigating high resource usage.
migrate
Create and manage database migrations using goose. Use for schema changes, new tables, or index optimization.
integration-test
Run integration tests that require Docker (Postgres, MinIO via testcontainers). Use to validate database and storage behavior.
generate
Run go generate to build templ templates and frontend assets. Use after changing templates or CSS/JS.
deps
Check and tidy Go module dependencies. Use after adding/removing imports or before releases.
coverage
Run tests with coverage analysis and identify untested code paths. Use to find gaps before releases.
check
Run pre-push quality checks (vet + lint + tests with race detector). Use before pushing code.
benchmark
Run Go benchmarks and compare results to detect performance regressions. Use before and after performance-related changes.