40,000 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
Add a new platform writer module in src/writers/ that generates and writes agent config files for a supported platform. Each writer exports a function that accepts a config interface, creates directories (rules/, skills/, mcp configs), writes files with proper formatting and frontmatter, and returns string[] of…
Build loop engineers: a file-based knowledge base your agents read/write (loops), plus a codebase harness (dev-local stack, e2e gate, an isolated cloud box per agent via crabbox, and verify-before-ship) so loops can run, test, and ship code autonomously. Plus an SEO growth playbook distilled from two production…
Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers.
Cross-agent memory layer with drift detection, Merkle integrity, semantic recall, and MCP A2A protocol. Surfaces user-facing slash commands for direct inspection of session memory.
★not rated 1.3k▲
+2
changed 20d agoA
tokens not measured
original
Shared base for gptaku plugins — routes each request to the matching gptaku skill (and, after /gptaku-core:setup, your own skills) before native WebSearch/WebFetch. Installed automatically as a dependency.
★not rated 1.2k▲
+24
changed 3d agoA
tokens not measured
originalMIT
Creates, converts, or modifies Teamskills — the multi-role extension of the Skills standard (specialized roles + workflow + bind constraints). Use when the user wants to author a multi-role agent team, convert a single-agent skill into one, or refactor an existing team. Do NOT use for single-agent Skills — use…
Taiwan knowledge for your AI, plus the skill that turns your machine into a Taiwan.md working node. The MCP server answers from 860+ curated, citation-backed articles in 12 languages — free, no API key, queries stay on your machine. The node skill picks up one open task a day and returns it as a pull request.
Reference for the shellm system — recursive LLM shell, identity management, memory, skills, trajectory, and all CLI tools. Use when working on shellm itself, debugging agent behavior, or understanding how the pieces fit together.
Defines practical standards for implementation-focused coding agents. Use when creating or editing code, especially when reliability, clarity, and low-risk delivery are required.
Full-auto AI-DLC pipeline in Hermes — from prompt to done. Automates the entire Idea -> Proposal -> Execute -> Verify lifecycle, with delegatetask wave execution and read-only delegatetask reviewers.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Create a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, coding, analysis, or content workflow into a distributable local SkillPack with skillpack.json, local skills under skills/, starter prompts, start scripts, and an optional zip package.
Optimized MCP server for AI coding agents. Structural codebase navigation + persistent memory engine — 97.9% accuracy at −80% tokens on tsbench. Runs locally from the token-savior-recall Python package. Needs 3 environment variables to run.
★not rated 1.2k▲
+7 10d agoA
tokens not measured
originalMIT
Runtime integration skill for external agents connecting to Todo for AI over HTTP API Token / Agent Key, including auth, task lease, events, commit, and task logs.
Plain-language skills for coding agents, for the person running development who does not read code: session reports, decisions, next steps and the whole picture.
This orchestration system is a highly advanced agentic meta-prompt designed for Claude Code. It enables skilled, autonomous coding workflows that can tackle complex tasks while iteratively self-improving. It combines an interactive planning phase (leveraging Claude Code's Plan Mode), dynamic multi-agent execution, and…
Create and validate Browser4 plugins, skills, JS scripts, and shell scripts; and develop Browser4 ITSELF (self-development): build modules, extract live skeletons, analyze impact, plan dev tasks, and check CDP pitfalls. Use when the user asks to write a Browser4 plugin or skill, write browser JS or build scripts…
Cavekit — compressed spec-driven dev. Full loop (grill → spec → research → review → build) over one SPEC.md file: three core commands + four reach-for. Caveman encoding. Bug-to-spec backprop.
★not rated 1.2k▲
+2 2mo agoA
tokens not measured
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: