AI Agent Tools

everything-claude-code266.3k★

Everything Claude Code (ECC) is a plugin you install through the Claude Code marketplace that bundles 63 agents, 249 skills, 79 commands, hooks, MCP server configs, and security enforcement scripts into one harness. The pitch is: stop hand-rolling your CLAUDE.md and skills, install this and get a curated set that actually works. It's MIT licensed and works across Claude Code, Cursor, OpenCode, and Codex, not just Claude. The agents cover the usual suspects (code review, security analysis, planning, language-specific reviewers) and the skills span TDD, video editing, and dozens of niche workflows. Hooks auto-execute on editor events. The security scanning piece tries to catch prompt injection and rule violations before they hit your codebase. Solo devs and small teams using AI coding agents get the biggest lift here. Pulling in 63 agents you didn't ask for is overkill, but cherry-picking the ones that match your workflow is the real value. Large teams will probably want to fork it and trim aggressively. The catch: 249 skills is a lot of surface area to audit. You're trusting someone else's prompt engineering to run inside your editor. Read the security-relevant pieces before you turn the hooks on, and treat this as a starting template, not gospel.

ponytail145.2k★

Ponytail is a plugin that talks your coding agent out of writing code. It installs a decision ladder the agent has to walk before it types anything: can this be skipped entirely, can existing code be reused, is there a standard library function, is there already a dependency that does it, can it be one line. Building something new is the last rung. MIT licensed, nothing to host. What started as a Claude Code skill now covers roughly twenty harnesses, each with its own install command: Codex, Copilot CLI, Cursor, Windsurf, Cline, Zed, Gemini CLI, Aider. Node on your PATH is the only hard requirement, for the lifecycle hooks. Six commands cover mode control, review, audit, tech debt, and a gain report, and three intensity levels dial how aggressive it gets. The project's own benchmark on FastAPI and React edits claims 54% fewer lines, 20% lower cost, and 27% faster runs. Treat a maintainer's benchmark as directional rather than settled. Solo developers: the token savings alone repay ten minutes of setup. Small and medium teams: worth standardizing so agent output looks the same across the team. Large teams should wire the audit and debt commands into review. The catch is that "write less code" is a preference, not a law. Push an agent hard enough toward minimalism and it will reach for a dependency that does not quite fit, or skip an abstraction you wanted. Start on lite, read what it declines to build, and turn it up once you trust its judgment.

gstack134.0k★

gstack is Garry Tan's (YC CEO) Claude Code workflow as a public repo. It ships 23 specialized agents that act like a virtual engineering team, plus slash commands like /office-hours, /review, and /ship that drive end-to-end product work from one terminal. The agents play roles: CEO, designer, engineer manager, QA lead, and more. The idea is that a solo dev orchestrates the team through commands instead of doing every job in series. TypeScript core with some Go for the parts that need speed. Everything lives in .claude/, nothing touches your PATH, and a persistent Chromium browser daemon handles visual testing and QA loops. MIT licensed. Solo devs and tiny teams are the target. If you're already shipping by yourself with Claude Code, this is a real upgrade. Bigger teams will trip over the opinionated roles, since you already have a real designer and QA lead and don't need an agent pretending to be one. The catch: this is one founder's workflow turned into a kit. If your style doesn't match Garry's, you'll fight the agents instead of using them. It's also Claude Code only. No Cursor, no Codex, no swap-in for other harnesses.

career-ops72.0k★

Career-Ops turns your AI coding CLI into a full job search command center. Paste a job URL and get back a structured report broken into blocks A through H, with a single 1 to 5 score reached by holistic judgement across five dimensions. It generates tailored, ATS-optimized PDF resumes per application. One developer used it to evaluate 740+ offers and land a Head of Applied AI role. The system gets smarter over time. It builds an interview story bank in STAR format, ships a scanner preloaded with 100+ companies and 45+ search queries, and can batch-evaluate offers in parallel using sub-agents. The dashboard is a Go TUI built on Bubble Tea, so you browse the entire pipeline from the terminal, and an experimental web UI is available as an opt-in alpha. Running it needs Node.js and Playwright for the PDF generation and portal scanning. Solo job seekers running any AI coding CLI: this is a force multiplier. It used to be Claude Code only, and now it also works with Gemini, OpenCode, Qwen, Grok, Codex, and Kimi, several of which have free tiers. It does not replace your judgment, it structures it. The human in the loop design means the AI evaluates and you decide. The catch: the tool is free, but it leans on an AI CLI underneath, so your real cost depends on which provider you pick and how hard you run it. The preloaded company list skews heavily toward AI and tech companies. And the first evaluations are rough until you feed it enough context about yourself.

agentic-awesome-skills46.6k★

This is a library of more than 2,000 reusable SKILL.md playbooks for coding agents. Skills are structured prompts that teach an agent a specific job (write tests, harden a web app, run a data pipeline), and the project installs them into Claude Code, Cursor, Codex, Gemini CLI, Kiro, OpenCode and others. MIT for the code, CC BY 4.0 for the content unless an upstream notice says otherwise, free. You install with npx agentic-awesome-skills plus a tool flag like --claude, and the installer now makes you choose: named skills, a risk, category or tag filter, or explicit consent for the whole catalog. The project itself says to start with a focused plugin instead. Newer releases add AAS Core, an optional local CLI and MCP server that lets an agent search the catalog and validate the skills it picks. For anyone building an agent workflow, this is a fast way to skip writing every skill from scratch. Solo developers and teams get the same value, since skills are just files you version alongside your project. The catch is curation. Thousands of community skills mean variable quality and overlap, and an installed skill is a prompt your agent will follow. The catalog labels some skills critical or offensive, and an audit command flags network, credential and destructive signals, but the project calls that a review aid, not a safety certificate. Read the ones you install.

watermarks-remover22.7k★

Watermarks-remover strips AI provenance marks from text and files: invisible Unicode watermarks (zero-width characters, bidi marks) from text, and C2PA manifests, EXIF, and XMP metadata from images, PDFs, and Office documents. It ships as an agent skill plus standalone Python scripts, MIT licensed, stdlib-only at the core. The legitimate use is real: invisible Unicode breaks diffs, search, and paste, and metadata on your own files is yours to remove. The honest part is what it admits it can't do. Deterministic removal covers Unicode and file metadata; statistical watermarks baked into AI text get best-effort rewriting that degrades the prose, and the project says so. Its own ethics doc rules out academic fraud and disclosure-dodging, and states plainly that a removed mark doesn't mean the content was never AI-assisted. Use it for hygiene on files you own. For pure image metadata work, exiftool and mat2 are the incumbents, and this wraps rather than replaces them. The catch: it cannot verify its own success against the strongest watermarks, and if your reason for reaching for it is a disclosure rule, the tool's own documentation tells you not to. It's also brand new, so treat the polish as unproven.

security-audit-skill21.0k★

Cloudflare's Security Audit Skill turns a coding agent into a vulnerability auditor. A skill is a module you add to an AI coding agent to give it a specific job. This one runs a six-phase audit: it maps your app, sends parallel agents to attack from different angles, then has separate agents try to disprove each finding before it gets reported. The philosophy is blunt, only report what you can actually exploit, with a concrete attack scenario, not a checklist of maybes. MIT licensed and free. There is no service to run. You install it into your agent with one command, npx skills add, and ask it to audit a codebase. The only real dependency is a coding agent that supports tool use and parallel sub-agents, plus Node for schema validation. The cost you do pay is model tokens, since the multi-phase, multi-agent design burns through a lot of them on a real codebase. The independent verification pass exists to cut false positives, which is the usual failure mode of AI security scanners. For solo developers and small teams without a security budget, this is a strong first pass and it is free. Larger teams should treat it as one input, not a replacement for a real pentest or a human reviewer. The catch: it is only as good as the agent running it and the tokens you feed it. It finds plausible issues and verifies them, but it does not replace someone who actually understands your threat model.

prompt-master13.2k★

Prompt Master writes the prompts for you. It's a Claude Code skill that generates accurate, context-aware prompts for any AI tool, optimized so you waste fewer tokens and get better output on the first try. The value proposition is simple: instead of trial-and-error with different prompt phrasings, you describe what you want and Prompt Master generates the prompt that actually works. It retains full context and memory across your session, so each prompt builds on what came before. MIT licensed. The catch: this is a skill that writes prompts for other AI tools, so you're adding an extra LLM call before every interaction. If your prompts are already working fine, this is overhead. And 'accurate prompts' is a bold claim. Prompt engineering is still more art than science, and what works for one model may not work for another.

skills10.4k★

This turns Sahil Lavingia's Minimalist Entrepreneur methodology into Claude Code skills. Ten of them install through the plugin marketplace: find a community, validate an idea, scope an MVP, processize, find first customers, set pricing, plan marketing, grow sustainably, define company values, and run a minimalist review. Instead of reading the book and trying to apply it, you invoke a skill and the agent, prompted to act as an advisor channeling the book's philosophy, walks your specific situation through the framework. It asks questions, works through your answers and hands back structured output. The skills are free; you need Claude Code to run them. The catch is that this is one founder's business framework, not a technical tool. Output is only as good as your inputs, and if you disagree with the minimalist approach you will disagree with the advice. The repo has not been updated since April and ships no LICENSE file, only an MIT declaration in its plugin manifest, so be careful about reusing the prompts.

dbskill10.2k★

dbskill is a pack of 30 business skills you install into a coding agent. Not code skills. Business ones: pricing diagnosis, competitor benchmarking, content topic development, headline and short-video hook optimization, decision logging. The content was mined from roughly 16,000 public tweets by the creator and distilled into structured knowledge the agent can call. Install is one npx command and it works with Claude Code, Codex, Dou Bao, WorkBuddy, and other agents that support the skills format. There is nothing to host and no API key of its own. One thing to know before you try it: the skills are written in Chinese, so the frameworks and the prompts you get back are in Chinese unless you translate them. The value is the structure rather than the intelligence. Instead of improvising a prompt every time you want to pressure-test pricing, you call a skill that already knows which questions to ask in which order. Solo founders and content creators are the real audience. Engineering teams will not find much here. The catch is the license, and it is a real one. This is CC BY-NC 4.0, which means non-commercial use only. Using these skills to run your own business is exactly the commercial use that license restricts, and you need separate authorization from the author. That is an odd shape for a business toolkit, so read the terms before you build a workflow on it.

awesome-codex-subagents6.2k★

This is a curated collection of subagents for OpenAI's Codex CLI, now past 170 entries across more than a dozen categories. Picture an app store of pre-built specialists: each subagent is a config file tuned for one job, testing, documentation, security review, database migration, and dozens more. You don't build these yourself. You browse the list, grab the ones that fit your workflow, and drop them into your Codex agents directory. They use Codex's native TOML format with Codex-specific fields like reasoning effort and sandbox mode. Codex does not spawn them automatically, you delegate to them explicitly. The collection is free. You pay for Codex usage through your OpenAI account. It is community-maintained and still growing, so the catalog keeps expanding. The catch: this is a curated list, not a framework. Quality varies across the entries. Some are polished, some are experiments. And it is Codex-only. It does not work with Claude Code, Cursor, or other AI coding tools, so the value evaporates the moment you switch assistants.

wewrite3.3k★

Wewrite is a Claude Code skill that handles trending topic research, topic selection, article writing, SEO optimization, and publishing. Built for the Chinese content market. The pipeline goes from identifying trending topics on Chinese social platforms to generating articles optimized for WeChat's distribution algorithm. It covers the entire workflow that content teams typically do manually across multiple tools. The catch: Chinese-language tool for a Chinese platform. If you don't publish on WeChat, this is not for you. AI-generated content at scale raises quality questions regardless of platform, and WeChat has its own content policies around automated publishing that you need to understand before running this at volume.

headcount1.7k★

headcount packages Claude Code skills the way a company packages people: 16 departments covering things like security, finance and engineering, 172 skills in total, each department installable on its own. Rather than dumping every skill into one project and hoping the model picks the right one, you add the departments a project needs. Skills are addressed as department:skill, so security:threat-modeling and finance:unit-economics never collide. MIT licensed. Installation is two lines in Claude Code: add the marketplace, install a department. There is no server, no runtime, and nothing to keep patched. The whole thing is Markdown, which is also the honest description of what you are installing. An interactive org chart on the project site lets you search every skill and jump to its source before you commit to any of it. Free, all of it, with no paid tier. Solo builders and small teams get the most value, since the appeal is scaffolding you did not have to write. Larger teams should read the skills they install rather than trusting the department label, because these become instructions your agent follows. The catch is that 172 skills is a claim about volume, not quality, and the project is very new. Skill collections rot fast as the underlying agent changes, and a stale skill that confidently tells your model the wrong process is worse than no skill at all. Install the two departments you need, not all sixteen.

pm-claude-skills1.4k★

pm-claude-skills is a library of ready-made skills you install into Claude Code or another AI agent to give it senior-professional workflows. Think PRDs, launch plans, and postmortems, around two hundred structured templates across twenty-plus fields, installed with one npx command and exportable to ChatGPT, Gemini, or Cursor. MIT, free. There is nothing to host; these are local Markdown files your agent reads. The value is entirely in the templates, so it lives or dies on whether the bundled frameworks match how you actually work. Across two hundred-plus skills the quality will be uneven, and a generic PRD template is only as useful as your willingness to adapt it. Treat it as a starting library, not gospel. This is for product managers and other knowledge workers using an AI agent who would rather start from a structured template than write every prompt from scratch. Solo or team, it is free. If you already have refined prompts you trust, or you bristle at one-size-fits-all frameworks, you will not get much from it. The catch is that this is content, not software. It does not make your agent smarter; it gives it scaffolding. Good scaffolding saves time. Generic scaffolding just adds a step. Skim what is in the box before you build a workflow around it.

autoprompt-skill1.3k★

Autoprompt is a skill that runs the loop for your coding agent. You hand it a goal, constraints, and success criteria, and it scopes, implements, tests, reviews, repairs, and verifies without you prompting each step. It installs into Claude Code, Codex, Copilot, OpenCode, and others through a single npm CLI. MIT licensed. The install story is the polished part. npm install -g autoprompt-skill, run autoprompt, pick your agent, confirm the path. A doctor --strict command checks every detected installation and uninstall is clean per provider, which is more lifecycle care than most agent skills bother with. It needs Node 20+, Python 3.11+ with PyYAML, and Bash 4.3+, so macOS and Linux unless you are in WSL. Free with no paid tier above it. The cost is tokens. A loop that implements, tests, reviews, and repairs makes many more model calls than you would by hand, and the project's own docs warn that on very small tasks the overhead works against you. The catch is how much weight the benchmark headline carries. The 45% fewer failures figure comes from a single Terminal-Bench 2.1 run, and the README says outright that timing and token logs were not retained, making the speed and cost numbers estimates from user reports. Credit for disclosing it. Measure on your own repo first.

guard-skills1.3k★

Guard-skills is a pack of quality gates for AI coding agents. You point your agent at them and they run a second pass over the code it just wrote, catching the specific ways AI-generated code tends to fail: swallowed errors, hardcoded "success" returns, hallucinated APIs, tests that assert nothing. Free and MIT licensed. Five skills cover the bases. One guards general clean code, one guards test quality (mock abuse, duplicate tests, implementation-detail assertions), and one treats your docs as claims and verifies each against the actual code. Two more are specific to WordPress and WooCommerce, handling escaping, sanitization, and money math. Install is a one-liner through the skills CLI, with nothing to host. If you let an AI agent write code, this is a cheap safety net for catching the slop before it ships. It's complementary to your real CI tooling, not a replacement for it. Useful at any team size, though heavier teams will still want proper linters and human review on top. The catch: it's brand new, just a couple of commits in, and tied to agents that support the skills format. Half the pack is WordPress and WooCommerce specific, so a general developer really gets three of the five skills. Worth watching as it grows.

ai-copywriter1.1k★

ai-copywriter is a prompt pack, not software. It's a portable agent "skill", a structured SKILL.md instruction set that teaches any capable LLM to write marketing copy using real copywriting frameworks and then strip out the tells that make text read as AI-generated. It bundles 33 specific fixes drawn from Wikipedia's "Signs of AI writing" list. Because it's instructions rather than code, it runs anywhere an agent runs: Claude, ChatGPT, Manus, whatever you've got. It's versioned, MIT licensed, and credits the upstream humanizer work it builds on, so it's a legit community project rather than a scraped prompt dump. For anyone using an AI assistant to draft landing pages, emails, or ads, it's a free upgrade to your output quality. Install it through the Skills CLI or as a Claude Code plugin and point your agent at it. The catch is exactly what it is: a Markdown file. There's no app, no guarantee, and results still ride entirely on the model you run it against. Treat it as a good starting prompt you'll still edit, not a copywriter in a box.

qiaomu-goal-meta-skill900★

qiaomu-goal-meta-skill is a skill for Claude Code and Codex that takes a vague request like 'build me an app' and turns it into a structured goal spec: clear success criteria, constraints, safety boundaries, and conditions where the agent should stop and ask. The point is to make an AI agent plan properly before it starts changing things. MIT, free, one command to install. There is nothing to run and no setup beyond adding the skill to your agent. It is narrowly scoped: it generates tight, bounded task specifications, with conservative defaults and pause-on-risk conditions baked in. It is also a young, single-commit project, and the documentation is primarily in Chinese with an English mirror, so set expectations accordingly. This is for people using a goal-style agent who keep getting burned by under-specified prompts and want guardrails between 'I have an idea' and 'the agent is editing files.' Solo or team, it is free. If you already write detailed, bounded task specs by hand, or you do not use a compatible agent, you will not get much from it. The catch is scope and maturity. It does one specific thing, generate disciplined goal specs, and it only helps inside a compatible agent. Treat it as a useful habit-former for agentic work, not a finished framework.

compass-skills737★

compass-skills is a set of Markdown skills that help an AI coding agent manage long, multi-session work. It gets the agent to clarify the task, keep a repo-local memory of goals as a kind of task tree, hand off context cleanly between sessions, and follow your collaboration preferences. Everything stays in local plaintext, nothing is uploaded. MIT, free. There is nothing to run and no remote piece; the state sits as plaintext in your repo. It is narrowly aimed at the problem of agents losing the thread across long projects and multiple sessions. It is also very new, a couple of weeks old and mostly one author, so the conventions may shift and longevity is unproven. Early but pointed at a real pain. This is for developers running Claude Code or Codex on long-running projects who keep losing context between sessions and want persistent task memory. Solo or team, it is free. If your work is short and single-session, or you do not want to adopt another agent convention layer, skip it. The catch is maturity. The idea, giving an agent durable memory and clean handoffs, is a real one, but this is an early, single-author project, so bet on the concept more than the specific implementation. If it sticks, great; if it stalls, you have not lost much.