Scan source projects with compilers and linters to produce prioritized diagnostic reports.
npx skills add https://github.com/thistleknot/skills --skill diagnostic-scanner
Please help me install this Agent Skill. Skill: diagnostic-scanner Source: https://github.com/thistleknot/skills/tree/main/diagnostic-scanner Command: npx skills add https://github.com/thistleknot/skills --skill diagnostic-scanner
diagnostic-scanner eliminates the time-consuming work of manually running linters and compilers, interpreting noisy logs, and producing a clear, prioritized list of actionable issues.
Use the diagnostic-scanner skill to scan a project folder and generate a markdown diagnostic report with grouped errors and warnings ready for LLM-based fixes.
High-intent search queries and answers about installing and using this skill.
Generate a fix-ready markdown diagnostic report by scanning your project with language-appropriate compilers and linters. The report normalizes tool output into structured findings grouped by severity with file and line context, including embedded JSON metadata for automated repair workflows.
Yes, you can use static analysis and linting for CI/CD gatekeeping across multiple languages. The scanner selects appropriate diagnostics tooling per detected language, such as mypy for Python, go vet for Go, cargo for Rust, and tsc for TypeScript.
Generate LLM fix prompts from code compilation errors by parsing and normalizing compiler output into a markdown report containing fix-ready context with embedded JSON metadata. This structured format provides downstream LLM workflows with the exact file and line context needed for automated repair.
Yes, the diagnostic scanner optionally includes test compilation results in the code quality report. This feature is represented in the skill's interface and contract to support comprehensive automated code quality checks alongside standard linter and compiler findings.
The best way to automate code fixes from noisy linter logs is to normalize the output into structured findings grouped by severity. This eliminates manual log interpretation and produces a clear, prioritized list of actionable issues with embedded JSON metadata for automated repair.
Automated code quality checks support Python, Go, Rust, and TypeScript/JavaScript by invoking language-appropriate diagnostics tooling such as mypy, pylint, go vet, golangci-lint, cargo, tsc, and eslint to parse output into consistent findings.
JongsixAutomate LSP diagnostics, AST-grep scanning, and test validation loops for changed source files.
nateaCalculate and visualize software quality metrics for dashboards and CI/CD quality gates.
softmgAutomate GitHub Actions workflow generation and CI/CD pipeline management.
VMAFxRun multiple static analysis tools and merge findings into one report.
