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dev-skills

License: MIT Skills Tool

Your AI coding assistant will hallucinate an API that doesn't exist, break file B while fixing file A, weaken your tests until they pass, and silently drop fields during data conversion. Most AI "skills" are 50-line rule snippets that can't prevent any of this.

dev-skills are multi-phase execution systems — with quality gates, error recovery, and systematic mitigation of 8 known AI weaknesses — covering the entire software lifecycle from project scaffolding to store launch.

Quick start: git clone https://github.com/sungurerdim/dev-skills.git /tmp/ds && cp -r /tmp/ds/ds-review ~/.claude/skills/ds-review && rm -rf /tmp/ds Then: /ds-review

What we believe

  • Every dependency is a future breaking change. Fewer deps = fewer risks, fewer costs, fewer breakages.
  • Collect nothing you don't need. Privacy-by-design, data minimization, zero unnecessary collection.
  • If a human is doing it repeatedly, it should be automated. No manual repetitive work.
  • Every decision minimizes YOUR legal exposure. Not the vendor's.
  • One developer + AI should ship what a team of five ships. Every skill optimized for solo devs with AI.

The skills

scaffold → code → test → review → commit → PR → deploy → launch → analytics

Skill What it does
ds-init New projects start with no CI, no tests, no linting. Scaffolds all of it from day one.
ds-fix AI skips formatting and ignores lint. Runs all 5 quality passes in the correct order.
ds-test AI tests mock everything and assert nothing. Generates tests that follow your patterns and pass.
ds-review Catches what tests miss — security holes, dead code, wrong abstractions. File:line precision.
ds-blueprint Can't improve what you don't measure. Scores your project across 9 dimensions.
ds-docs Docs drift from code the moment they're written. Detects gaps and verifies claims against source.
ds-commit AI commits are vague and bundle unrelated changes. Reads the diff, groups logically, writes precisely.
ds-pr PRs that list every commit create noise. Describes the net diff, not the journey.
ds-deploy First deploy means bloated images, no health checks, no SSL. Generates production-ready configs.
ds-launch ~40% of store submissions fail for preventable errors. Scans your project and flags them.
ds-compliance One missing privacy policy or unpatched XSS means fines or rejection. 80+ rules, file:line precision.
ds-mobile Permission abuse, missing a11y, hardcoded keys surface during review. 145+ rules catch them first.
ds-devops Broken CI, unsigned builds, outdated deps erode release quality. Audits your entire DevOps setup.
ds-repo Unprotected branches, stale PRs, no CODEOWNERS — most repos are misconfigured. Audits and fixes.
ds-backend AI APIs ship with inconsistent naming and no auth strategy. Designs all three layers correctly.
ds-research AI hallucinates sources and cites outdated data. Searches, scores reliability, cites everything.
ds-market Solo devs build great products but can't get noticed. Generates positioning, copy, and growth playbook.
ds-analytics Most apps track everything (privacy risk) or nothing (blind). Designs minimum taxonomy, maximum insight.
ds-cv ATS rejects most CVs before a human sees them. Generates ones that pass.
ds-autotune Manual optimization: 8 experiments/day. This skill runs 100+ overnight, keeping only what improves.

Each skill is self-contained. No dependencies between them. Install one or all.

Recommended workflow

1. /ds-blueprint        Score your project health, generate .ds-findings.md
2. /ds-review --tactical  Fix code issues (uses .ds-findings.md if available)
3. /ds-fix              Format, lint, type-check
4. /ds-test             Generate missing tests, fix failing ones
5. /ds-commit           Commit with quality gates
6. /ds-pr               Create PR with net diff analysis

Start with /ds-blueprint — it scans your entire codebase and produces a .ds-findings.md that other skills consume, so they skip redundant analysis and jump straight to fixes.

For new projects: /ds-init → then the workflow above. For deployment: /ds-deploy/ds-launch. For audits: /ds-compliance or /ds-mobile.

Why these are different

Most AI coding "skills" are static rule snippets (30-100 lines). dev-skills are orchestrated execution systems:

  • Multi-phase workflows with quality gates, mandatory phase enforcement, and error recovery
  • 8 AI weaknesses systematically addressed — hallucination, scope creep, tunnel vision, confidence bias, memory decay, skip tendency, redundancy blindness, injection risk
  • Finding Resolution Completeness (FRC) — every finding gets a disposition (fixed/skipped/failed), zero silent drops
  • Inter-skill coordination via .ds-findings.md + blueprint profile — share analysis results and project context, avoid duplicate work
  • Token-efficient — 10K token budget per skill, references loaded on demand
  • Tool-agnostic — works with any AI tool that accepts markdown instructions

Install

Copy any skill folder to your AI tool's instructions directory:

git clone https://github.com/sungurerdim/dev-skills.git /tmp/dev-skills
Tool Install
Claude Code cp -r /tmp/dev-skills/<skill> ~/.claude/skills/<skill>
Cursor Copy SKILL.md + references/ to .cursor/rules/
GitHub Copilot Append SKILL.md content to .github/copilot-instructions.md
Windsurf Append SKILL.md content to .windsurfrules
Aider Reference SKILL.md via --read flag
rm -rf /tmp/dev-skills

How skills work

skill-name/
  SKILL.md        ← Instructions and execution flow
  README.md       ← What it does, how to use it
  references/     ← Detailed rules (loaded on demand)

Each skill is a multi-phase execution system. Phases have explicit entry conditions, quality gates, and error recovery. The references/ files contain detailed rules loaded on demand — total skill overhead stays within 10K tokens.

Build your own

All skills follow SKILL-SPEC.md — a universal specification for building tool-agnostic, token-efficient AI coding skills.

See also: AI Instruction Patterns — research-backed best practices for writing effective AI agent instructions.

Companion: dev-rules

Always-on behavioral guardrails that prevent mistakes between skill invocations — scope control, complexity limits, security gates, operational awareness. One file, any AI tool: dev-rules.

Contributing

See CONTRIBUTING.md.

License

MIT

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Your AI assistant hallucinates APIs, breaks dependent files, and weakens tests. 20 skills that prevent this across the full software lifecycle.

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