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laravel-verification

Verification loop for Laravel projects: env checks, linting, static analysis, tests with coverage, security scans, and deployment readiness. Use when verifying a Laravel project before merge or deploy — lint, static analysis, tests, coverage, security.

Was ist laravel-verification?

laravel-verification is a Claude Code agent skill that verification loop for Laravel projects: env checks, linting, static analysis, tests with coverage, security scans, and deployment readiness. Use when verifying a Laravel project before merge or deploy — lint, static analysis, tests, coverage, security.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/laravel-verification

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Dokumentation

Laravel Verification Loop

Run before PRs, after major changes, and pre-deploy.

When to Use

  • Before opening a pull request for a Laravel project
  • After major refactors or dependency upgrades
  • Pre-deployment verification for staging or production
  • Running full lint -> test -> security -> deploy readiness pipeline

How It Works

  • Run phases sequentially from environment checks through deployment readiness so each layer builds on the last.
  • Environment and Composer checks gate everything else; stop immediately if they fail.
  • Linting/static analysis should be clean before running full tests and coverage.
  • Security and migration reviews happen after tests so you verify behavior before data or release steps.
  • Build/deploy readiness and queue/scheduler checks are final gates; any failure blocks release.

Phase 1: Environment Checks

php -v
composer --version
php artisan --version
  • Verify .env is present and required keys exist
  • Confirm APP_DEBUG=false for production environments
  • Confirm APP_ENV matches the target deployment (production, staging)

If using Laravel Sail locally:

./vendor/bin/sail php -v
./vendor/bin/sail artisan --version

Phase 1.5: Composer and Autoload

composer validate
composer dump-autoload -o

Phase 2: Linting and Static Analysis

vendor/bin/pint --test
vendor/bin/phpstan analyse

If your project uses Psalm instead of PHPStan:

vendor/bin/psalm

Phase 3: Tests and Coverage

php artisan test

Coverage (CI):

XDEBUG_MODE=coverage php artisan test --coverage

CI example (format -> static analysis -> tests):

vendor/bin/pint --test
vendor/bin/phpstan analyse
XDEBUG_MODE=coverage php artisan test --coverage

Phase 4: Security and Dependency Checks

composer audit

Phase 5: Database and Migrations

php artisan migrate --pretend
php artisan migrate:status
  • Review destructive migrations carefully
  • Ensure migration filenames follow Y_m_d_His_* (e.g., 2025_03_14_154210_create_orders_table.php) and describe the change clearly
  • Ensure rollbacks are possible
  • Verify down() methods and avoid irreversible data loss without explicit backups

Phase 6: Build and Deployment Readiness

php artisan optimize:clear
php artisan config:cache
php artisan route:cache
php artisan view:cache
  • Ensure cache warmups succeed in production configuration
  • Verify queue workers and scheduler are configured
  • Confirm storage/ and bootstrap/cache/ are writable in the target environment

Phase 7: Queue and Scheduler Checks

php artisan schedule:list
php artisan queue:failed

If Horizon is used:

php artisan horizon:status

If queue:monitor is available, use it to check backlog without processing jobs:

php artisan queue:monitor default --max=100

Active verification (staging only): dispatch a no-op job to a dedicated queue and run a single worker to process it (ensure a non-sync queue connection is configured).

php artisan tinker --execute="dispatch((new App\\Jobs\\QueueHealthcheck())->onQueue('healthcheck'))"
php artisan queue:work --once --queue=healthcheck

Verify the job produced the expected side effect (log entry, healthcheck table row, or metric).

Only run this on non-production environments where processing a test job is safe.

Examples

Minimal flow:

php -v
composer --version
php artisan --version
composer validate
vendor/bin/pint --test
vendor/bin/phpstan analyse
php artisan test
composer audit
php artisan migrate --pretend
php artisan config:cache
php artisan queue:failed

CI-style pipeline:

composer validate
composer dump-autoload -o
vendor/bin/pint --test
vendor/bin/phpstan analyse
XDEBUG_MODE=coverage php artisan test --coverage
composer audit
php artisan migrate --pretend
php artisan optimize:clear
php artisan config:cache
php artisan route:cache
php artisan view:cache
php artisan schedule:list

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

api-connector-builder

Build a new API connector or provider by matching the target repo

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