Extract actionable patterns, architecture decisions, code conventions, and skill-relevant insights from GitHub/GitLab repositories. Assess repo credibility, run the full security scan pipeline, and apply findings to existing skills, new skills, or the current project. Load when the user asks to learn from a repo, extract patterns from a codebase, study a repository, or analyze a repo for reusable techniques. Also triggers on "learn from this repo", "learn from this repository", "what can we learn from this codebase", "extract patterns from this repo", "study this repo".
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Audit, improve, and compress every skill in the repo using live research. Load when the user asks to improve skills, audit the skill library, upgrade existing skills, refresh with new research, do a skill health check, or says "improve all skills", "update the skill library", "skill audit", or "run an improvement pass". Applies live domain research, fixes structural gaps, checks for skill linking opportunities, then rewrites and resizes each skill. Supports TARGETED mode (`TARGET=<skill> [SKIP_RESEARCH=true]`) for single-skill fixes, including learn-from-chat restructure escalations. All skills are in scope including meta skills.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Audit project and global memory for bloat, stale decisions, duplicates, contradictions, unsafe content, missing provenance, broken routing, and over-budget global files. Load when the user asks to audit memory, clean memory, check memory health, or verify memory quality.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Score an unbuilt business idea on desirability, viability, feasibility, distribution wedge, why-now, founder-market-fit, market size, alternatives, defensibility, capital intensity, and regulatory/ethical risk — and return a GO / ITERATE / KILL verdict with kill criteria and a next kill test. Load when the user asks to evaluate a business idea, score a startup idea, screen an idea, decide whether to pursue this venture, do an idea review, or says "is this a good business idea", "should I build this", "evaluate this startup", "screen this idea", "go/no-go on this idea", "kill or pursue". Sub-skill of `venture-exploration`. Calls `fermi` for sizing, `assumption-mapping` for hidden beliefs, optional `pre-mortem` / `adversarial-hat` for high-stakes ideas. Does NOT evaluate built products — for that use `reality-check`.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Extract actionable skill knowledge from academic papers and research articles, assess credibility, run security checks, and either improve existing skills or create new ones. Load when the user asks to learn from a paper, extract insights from a research paper, turn a paper into a skill, apply paper findings to skills, read this paper and improve my skills, or process a research article. Also triggers on "skill from paper", "learn from this paper", "paper to skill", "extract from this research", "apply this paper", or when the user uploads or links to an academic PDF or paper URL.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Build, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Extract actionable insights from blog posts, web articles, and practitioner content - assess credibility, run security checks, and either improve existing skills or apply to the current project. Load when the user asks to learn from an article, extract insights from a blog post, apply a practitioner's findings, or process engineering blog content. Also triggers on "learn from this article", "learn from this blog post", "extract insights from this post", "what can we learn from this article", "apply this article", or when the user links to a blog, Medium, Substack, dev.to, or engineering blog post.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Flip a problem, goal, or decision 180 degrees to find what forward thinking misses. Asks what would guarantee failure, then works backward to what must be avoided or changed. Load when the user says "invert this", "flip this problem", "what would guarantee failure", "think backward", "reverse engineer the goal", "think about it backwards", or when deep-thinking diagnoses an inversion frame. Also triggers on "what's the opposite of success here", "how would we sabotage this". Two methods: Failure Inversion and Opposite Goal. Max 2 clarifying questions before inverting. Always returns forward actions. For broader analysis, deep-thinking calls this.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Build GSAP JavaScript animations for web apps — timelines, scroll-driven motion, SVG draw/morph/path effects, and React integration with useGSAP. Load when the user asks to animate with GSAP, add ScrollTrigger, draw SVG paths with GSAP, morph SVG shapes, sequence page animations, or wire GSAP in React/Next/Vue. Also triggers on "GSAP timeline", "DrawSVG", "MotionPath", "gsap.context", or "scroll animation library". Not for self-contained README/GitHub SVG files.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Orchestrate persistent agent memory across coding sessions, repos, and tools. Load when the user asks to remember, recall context, save project memory, create a handoff, manage global memory, update memory, compact memory, audit memory, forget memory, continue from prior sessions, or before commit/push/git operations that checkpoint project state.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Research a skill domain before building or improving a skill. Searches academic papers, practitioner blogs, and GitHub skill repos in parallel to find current best practices, domain gotchas, and existing skill patterns. Called by universal-skill-creator and improve-skills before writing any skill. Also load directly when the user asks to research a domain for a skill, find existing skills on a topic, discover best practices for a skill, check what research exists before building an agent skill, or says "what does current research say about", "find best practices for".
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Design a self-improvement loop for a shipped product's AI agents — production traces feed evals, evals feed improvement proposals (prompts, playbooks, retrieval configs), and a human approval gate promotes changes with rollback. Technique-agnostic: chooses per project between ACE-style evolving playbooks, GEPA/MIPROv2 offline optimization, or simple eval-driven iteration via references/techniques.md. Load when the user asks to make my product's agents self-improving, learn from production traces, add a learning loop, evolve prompts or playbooks safely, promote agent improvements, or GEPA-style optimization. NOT harness-evolution (that improves the coding agent), NOT experimentation (product A/B tests), NOT agent-run-retro (dev-phase manual retros — this skill is the production-scale continuation).
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Build Motion (Framer Motion) React animations — declarative motion components, variants, AnimatePresence, layout transitions, scroll effects, and inline SVG pathLength. Load when the user asks to animate with Motion, Framer Motion, motion.div, AnimatePresence, layout animation, whileInView, or React enter/exit transitions. Also triggers on "framer-motion", "motion/react", "useReducedMotion", or "React animation library". React/Next only — not README embeds or non-React.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Measure, profile, and fix performance bottlenecks — Core Web Vitals, backend latency, bundle size, and database queries. Load when performance requirements exist, users report slowness, profiling reveals bottlenecks, or the user asks to optimize load time, LCP, INP, CLS, or response time. Not for premature optimization without evidence. Pairs with browser-testing-with-devtools and ci-cd-and-automation for regression guards.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Evaluate any project, product, or system's claims against its actual implementation — scoring each claim for truth, identifying architectural gaps, assessing competitive positioning, proposing creative solutions, and producing an actionable roadmap. Load when the user asks to evaluate claims, reality-check a project, assess what this project actually does vs what it says, validate product claims, or score a system's credibility. Also triggers on "is this real", "does this work as claimed", "evaluate this project", "assess the gap between claims and reality", "how credible is this", "investor assessment", "score these claims", or "what's real vs marketing".
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Generate a tailored AGENTS.md for any new project by interviewing the user about their skill gaps, project goals, and tech context. Load when the user asks to set up a project, initialize agents, create an AGENTS.md, bootstrap a repo, onboard agents to a codebase, or says "set up this project for agents". Also triggers on "write an AGENTS.md for this project", "configure agents for my repo", "project bootstrap", "agent onboarding", or when the user starts a new project and needs agent-ready configuration. Re-run when new context arrives (PRD written, stack changes, team changes) to update the AGENTS.md.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Guided first-run that produces a real verified win in under five minutes using the skill library on a seeded offline fixture. Load when a new user asks how to start, run the demo, try agent-loom, or get a quick win. Also triggers on "quickstart", "first run", "demo agent-loom", "try the skills", or onboarding to the library. Zero external credentials required. Idempotent — safe to run multiple times.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Apply one logical code change with mandatory impact mapping, git snapshot, verification, and automatic revert on failure. Load when the user asks for a safe edit, verified change, one change at a time with rollback, or codespine-style edit loop. Also triggers on "safe change", "edit with verification", "don't break the build", "revert if tests fail", or any non-trivial code edit where blast radius matters. Always runs dependency-mapping first. Pairs with incremental-implementation for multi-slice work; this skill is one atomic verify cycle per invocation.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Author the project's non-negotiable engineering rules — the constitution that every feature spec, plan, and implementation must satisfy. Load when the user asks to write a constitution, define project rules, set engineering invariants, write project standards, define non-negotiables, capture agent guardrails as policy, or when spec-driven-development orchestrator routes here. Also triggers on "project constitution", "engineering invariants", "non-negotiable rules", "project policy", "set our standards", "/constitution". Output: docs/constitution.md. The third strategic artifact alongside AGENTS.md (agent behavior) and product-soul (strategy).
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Write concise next-agent handoff summaries across sessions, tools, and coding agents. Load when the user says handoff, next agent should know, save context, summarize where we are, switching agents, before ending a meaningful session, or when the user asks to commit, push, commit and push, create a git commit, push to origin, or publish commits — commit/push requests MUST run this skill first to prepare handoff docs, then proceed with git operations.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Run a structured discovery interview and produce a complete, developer-ready Product Requirements Document. Load when the user asks to write a PRD, create product requirements, document a feature, define user stories with acceptance criteria, or turn a rough idea into a formal product requirements document. Also triggers on "document this feature", "write requirements for", "create a one-pager", "turn this into a PRD", "I need a PRD for", or any request to produce a structured product document for stakeholder alignment or engineering handoff. Supports Full PRD, Lean PRD, and One-Pager formats. Note: for executable feature specifications (FRs, NFRs, ACs as Given/When/Then consumable by AI coding agents), route to `feature-spec` instead — PRDs frame the product, feature-specs encode the implementable contract.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Package and publish a skill to the skills.sh community registry, a public GitHub repo, or both. Load when the user asks to publish a skill, share a skill publicly, submit a skill to the registry, release a skill, or when universal-skill-creator offers publishing as a final step after creation. Also triggers on "push this skill to skills.sh", "make this skill public", "share this skill", or "contribute this skill to the community". Validates quality before publishing, packages correctly (zip for multi-file, .md for atomic), writes a README if missing, and publishes via npx skills CLI.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新
Write a Product Soul document — the strategic north star that sits above any PRD or feature spec. Captures the product's reason for existing across five lenses: user, business, strategy, product-market fit, and GTM distribution. Load when the user asks to write a product soul, product strategy doc, product north star, product positioning doc, product one-pager, or "why we exist" document. Also triggers on "write the soul of this product", "product strategy document", "what is this product really about", "capture the product vision", or when an agent needs strategic context before making product decisions. The output is docs/product-soul.md — a living document that brainstorming, prd-writing, and inversion can reference for grounding.
日本語の概要は準備中です。原文の説明を表示しています。
dvy1987/agent-loom☆ 32026年8月8日 更新