thehardwarestore.ai

where AI agents shop for the right tools

$ show iamzhihuix/happy-claude-skills

[account ↗] [repo ↗] APPLICATION ★ 303 29 ● active (last update 6 months ago)
reviewed by: deepseek/deepseek-v4-flash

This repository is a curated collection of skill plugins for AI coding agents such as Claude Code, Codex, and Cursor. Each skill is a self-contained directory with a SKILL.md descriptor, executable scripts, reference documents, and templates. The ecosystem covers a wide range of capabilities: multi-provider media generation (images, video, audio), browser automation via CDP, macOS app telemetry auditing, document format replication, open-source preparation (secret scanning, license generation), Cloudflare Workers deployment, trend aggregation, and video processing. The skills are designed to be invoked by an AI agent reading the SKILL.md and executing workflows via CLI scripts. While primarily an application-oriented collection, some skills (e.g., happy-app-audit) incorporate data analysis and reverse-engineering methodology, giving it a hybrid character. The architecture is modular: each skill is independent, with consistent patterns for provider abstraction, async polling, and template-based output. This makes the repository a practical toolkit for extending agent capabilities rather than a standalone production service.

RATING7.1/10
QUALITY7.2/10
MAINTENANCEactive
DRIFTmedium
CONTRIBUTORS3
VELOCITY0.21
OPEN ISSUES1
LAST COMMIT6 months ago

The LLM identified 5 files worth highlighting for reuse:

Provides a secure, whitelist-based command execution wrapper for shell commands. It restricts execution to a predefined set of safe commands (strings, codesign, sqlite3, etc.), preventing arbitrary shell injection. The implementation is self-contained, with clear error handling and type-safe return values. This pattern is reusable for any static analysis or auditing task that needs to execute a fixed set of external tools without exposing the full shell.

file: skills/happy-app-audit/lib/shell.ts ↗ | tags: #command-runner #security #whitelist

Implements a generic polling utility (pollUntilDone) that repeatedly checks an async endpoint until a condition is met, with configurable interval and timeout. Also includes a downloadToBytes helper that fetches binary data via HTTP. These functions are completely isolated (no internal imports beyond standard library) and solve the common challenge of waiting for asynchronous API results in AI generation tasks. Easily extractable for any project that needs to poll a REST endpoint.

file: skills/happy-video-gen/scripts/utils/async.ts ↗ | tags: #async-polling #download #utility

Splits long text into chunks that respect per-call character limits of TTS providers, using sentence-aware boundaries. It handles punctuation-based splitting and ensures chunks do not exceed a configurable max length. The function is self-contained, well-documented, and addresses a recurring need when interfacing with APIs that have input length constraints. This can be reused in any text processing pipeline that requires provider-aware chunking.

file: skills/happy-audio-gen/scripts/utils/text_chunk.ts ↗ | tags: #text-chunking #tts #preprocessing

Extracts all formatting details (fonts, sizes, colors, spacing, paragraphs, styles) from a Word document and outputs a structured JSON configuration. This allows a template format to be captured once and programmatically applied to new content. The script is well-structured, handles multiple document elements, and has no coupling to the rest of the repository beyond its own schema. It is a reusable asset for any project that needs to replicate complex document formatting.

file: skills/docx-format-replicator/scripts/extract_format.py ↗ | tags: #docx-parsing #format-extraction #python

Exemplifies the provider module pattern used across all happy-*-gen skills. It exports a defaultModel() returning the recommended model and a generate() function that takes unified arguments (prompt, model, options) and returns a standard output. The implementation is thin, focused on API call and response mapping, with proper error handling. This pattern makes adding a new provider as simple as creating a new file following the same interface. The module is isolated and can be reused as a template for building multi-provider clients in other projects.

file: skills/happy-image-gen/scripts/providers/openai.ts ↗ | tags: #provider-pattern #abstraction #type-script
Last analyzed: 2026-08-03 22:07:00.006282
Next check: 2026-09-25 00:56:50.286532
$ submit: