What is a Technical.md file?

A Technical.md file is a documentation standard used by the Candid toolset to define project-specific coding rules, architectural patterns, and constraints for AI developers.

Can it automatically fix my documentation?

Yes, by running the skill with the --fix flag, it provides specific suggested rewrites for vague or ineffective rules found in your Technical.md.

Why are vague terms like 'clean code' flagged?

Vague terms are subjective and difficult for AI or team members to enforce consistently. The skill encourages replacing them with measurable criteria like line counts or specific patterns.

How does this skill detect linter overlaps?

The skill scans your repository for configuration files such as .eslintrc, ruff.toml, or .rubocop.yml to identify rules already handled by automated tooling.

Candid Technical Standards Validator

Name: Candid Technical Standards Validator
Author: ron-myers

byron-myers

•

Developer Tools

Analyzes and optimizes Technical.md project standards by identifying vague rules, linter redundancies, and unverifiable requirements.

About

The candid-validate-standards skill ensures that your project's Technical.md file contains actionable, specific, and enforceable guidelines rather than subjective platitudes. By scanning for common pitfalls like missing thresholds (e.g., "short functions") and redundant linter rules (e.g., "use semicolons"), it helps developers create high-quality documentation that Claude and other AI tools can accurately follow during code reviews. It provides structured reports and actionable rewrites to transform fuzzy "best practices" into concrete technical constraints that improve overall code quality.

Key Features

Flags multi-concern rules that should be split into atomic requirements
Identifies missing numeric thresholds for function length and nesting depth
14 GitHub stars
Detects vague terminology like 'clean' or 'proper' that lacks specific criteria
Cross-references project configs like ESLint and Ruff to remove redundant rules
Generates suggested rewrites to improve the enforceability of project documentation

Use Cases

Auditing existing project documentation to improve AI-assisted code reviews
Cleaning up legacy Technical.md files that conflict with modern linter settings
Establishing high-quality, verifiable technical standards for new repositories

About

Key Features

Flags multi-concern rules that should be split into atomic requirements
Identifies missing numeric thresholds for function length and nesting depth
14 GitHub stars
Detects vague terminology like 'clean' or 'proper' that lacks specific criteria
Cross-references project configs like ESLint and Ruff to remove redundant rules
Generates suggested rewrites to improve the enforceability of project documentation

Use Cases

Auditing existing project documentation to improve AI-assisted code reviews
Cleaning up legacy Technical.md files that conflict with modern linter settings
Establishing high-quality, verifiable technical standards for new repositories