35,491 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.
This skill guides materials engineering researchers through four structured stages — from a raw idea to a fully planned experiment — with human-in-the-loop confirmation at each critical checkpoint.
Whether, then how, then shipped. /ideation:brainstorm pressure-tests ideas in conversation; the evidence-gated interview, stress-tested by adversarial plan critics, turns a yes into an interactive HTML contract and Markdown specs; /ideation:autopilot runs all phases on a deterministic workflow engine. Watched runs…
★not rated 13 10d agoA
tokens not measured
originalMIT
Fable 5's working loop for hard tasks: decompose by verification boundaries, verify against the world, choose next by plan-change. Includes scout + refuter agents and a preflight script.
Build concise, decision-ready account briefs for account reviews, account planning, renewal or expansion reviews, and customer meeting preparation. Use when asked to summarize an account's commercial state, stakeholders, risks, upside, or next actions. Route single-opportunity inspection to deal-inspection-coach and…
ProductOS — a complete operating system for taking a product from idea to revenue with AI agents. Installs inside your app repo as productos/, optionally ships with a coach-composed programme plan, and runs four phases (Define, Design, Develop, Distribute), each with checklists, templates, and 38 skills that fill them.
Use when user explicitly requests planning with a scratchpad, or asks for persistent tracking of a complex task that the human can browse visually. Backs planning files with the scratch CLI so a pad's files are registered and viewable.
Turn AI software engineering into an auditable, on-disk state machine. A staged PDLC workflow (PRD, design, TDD, implement, review, ship, retro) enforces hard contracts — artifacts on disk, per-feature state machine, tests-before-code, objective checks from real command exit codes, single-shot auto-repair — so AI work.
★not rated 13▲
+1
changed yesterdayA
tokens not measured
originalMIT
A 7-step problem-solving discipline loop that gives any model structured thinking: classify the ask, define done, gather evidence, decide, act surgically, verify by observation, report outcome-first. Use when the user says 'fable-method', or proactively when starting any multi-step task that no task-specific skill…
Use this skill when the user wants to plan a SaaS product end-to-end — turn a one-line idea into a full blueprint with research, analysis, architecture, feature specs, frontend wireframes, phases, and a deep step-by-step build playbook for Claude Code. Triggers on phrases like "plan my saas", "/planmysaas", "build a…
Convierte una idea de feature en un spec.md completo, listo para SDD (Spec-Driven Development). Sigue el estándar de GitHub Spec Kit: historias priorizadas con criterios de aceptación en Gherkin, requisitos funcionales, entidades, criterios de éxito medibles y suposiciones. Céntrate en el QUÉ y el PORQUÉ, nunca en el…
Use this skill when the user wants to plan a piece of implementation work and add it to the lauren queue (the lauren todo / backlog). Typical phrasings include "add this to lauren", "add this to the lauren todo", "lauren this", "let's make a lauren plan for X", or "plan this with lauren". The plan is then executed…
Persistent spec management for AI coding workflows. Use this skill when the user explicitly mentions specs, forging, or structured planning: says "forge", "forge a spec", "write a spec for X", "create a spec", "plan X as a spec", "resume", "what was I working on", "spec list/status/pause/switch/activate", "implement…
Startup / AI-startup CTO who is also a top-tier individual contributor. Two modes: (1) greenfield — turn fuzzy business intent into a buildable design (brief.md, arch.md, specs/) through conversation; (2) brownfield — work hands-on inside an existing codebase: investigate, recommend, refactor, write features, debug…
Use this skill when the user wants to discover, inspect, install, or apply Skills Hub presets, kits, AGENTS.md policies, or skill packages for a project. It guides the agent to use the Skills Hub CLI to search presets, inspect their policy and selected skills, install them as kit artifacts, and apply them with…
Coordinate a team of AI agents through a shared folder of markdown files.
★not rated 12 5mo 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: