1.3万 件 ・ 関連度順
概要と使いどころ
Grilling session that challenges your plan against the existing domain model and sharpens terminology. Use when user wants to stress-test a plan against their project's language and documented decisions; propose documentation updates for approval as decisions crystallise.
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。
Anti-AI-slop design skill for greenfield pages, audits, redesigns, and design extraction from URLs or screenshots. Use when the user asks to build a new app or landing page, wants to redesign something, invokes Hallmark by name, or uses audit/redesign/study.
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。
Read-only file search and codebase exploration specialist. Use when you need to find files by pattern, search code with regex, navigate unfamiliar codebases, or understand code architecture without making changes.
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。
Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.
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。
Use when the user asks to switch AI role/mode/persona or uses role-trigger words such as Captain, Coordinator, 寫文章, 寫文章模式, 文章模式, 技術文章, 部落格, 出版, 預覽. Routes the request to Project Captain, Publishing Director, or Article Writing Mode, loads the matching keep memory when available, and applies the role's workflow without excessive roleplay.
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。
DEBUGGING SKILL — Read and analyze Cocos Creator project.log for runtime errors, warnings, and stack traces. USE FOR: any bug report, crash, UI glitch, TypeError, null reference, missing asset, CompositePanel mount fail, ChildPanel route fail, or screen spec wiring error. Load this skill FIRST before any runtime debugging session. DO NOT USE FOR: compile errors (use get_errors tool instead).
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。
Detect and resolve naming collisions, overlapping intent triggers, and insufficient intent diversity across the skill library. Load when a new skill is created (called by universal-skill-creator), during improvement passes (called by improve-skills), or when the user asks to deconflict skills, check for naming collisions, audit trigger overlap, review intent coverage, find duplicate triggers, check skill names, or says "are any skills too similar", "which skills overlap", "deconflict the library", "check for confusing skill names", "intent audit".
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。
Pick an icon strategy and produce a coherent icon set that doesn't look mass-produced. Solves the "Lucide everywhere" problem — every AI-generated UI uses the same 24px stroke-1.5 outline icons, which is the second-biggest vibecoded tell after Inter-on-purple-gradient. Generates custom SVG sets, tunes existing icon libraries to match archetype + typography, defines stroke weight, optical sizing, and corner-radius rules. Load when the user asks to pick icons, design an icon set, customize Lucide / Phosphor / Heroicons, generate SVG icons, make icons feel custom, says "the icons look generic", "design a custom icon system", "icons for this product", or when frontend-design routes here during icon craft. Sub-skill of frontend-design.
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。
Think through the consequences of consequences — not just what happens immediately, but what happens next, and next after that, across time. Load when a decision looks obviously good or obviously bad on initial read, when the user is optimising for a short-term outcome that might create a long-term problem, when unintended consequences are a concern, or when deep-thinking diagnoses a second-order frame. Triggers on "what are the downstream effects", "what happens after that", "unintended consequences", "think ahead on this", "long-term vs short-term", or "what comes after that". Based on Howard Marks second-level thinking and Farnam Street mental models. Most powerful for decisions with delayed consequences or systemic effects.
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。
Runtime security for agent skills — prevents state corruption, skill overwrite attacks, denial of service, and enforces provenance tracking and no-go repo management. Load as part of the secure-* skill sequence whenever an agent processes external content or writes to the skill store. Also load when the user asks to check for state corruption, prevent skill overwrite, manage no-go repos, check provenance, audit runtime security, detect DoS patterns, or protect the skill store. Covers Issues 6, 9, 10 from the agent security threat model: instruction hierarchy enforcement, state corruption and skill overwrite, and denial of service prevention.
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。
Break a stuck or complex problem into the smallest sub-question that, if answered, unlocks the next step — then answer it and repeat until the path forward is clear. Load when a problem feels genuinely stuck, when reasoning keeps circling, or when deep-thinking diagnoses a Socratic frame. Also triggers on "I keep going in circles", "what is the real question here", "help me reason through this step by step", "unstick my thinking", "recursive questioning", "what is the root question". Based on the recursive Socratic questioning method (EMNLP 2023) which outperforms CoT and Tree-of-Thought on complex reasoning tasks.
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。
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。
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。
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。
Capture actionable learnings that emerge during conversation — when the agent or user discovers that a skill, a set of skills, or a process needs to be updated based on what's happening in the current chat. Sub-skill of the learn-from orchestrator. Load when the user says "we should update the skill for this", "this should be a skill rule", "add this as a gotcha", "the skill should know about this", "update the process for this", "remember this for next time", "this is important for the skill". Also triggers when the agent notices a skill's guidance was wrong or incomplete, a process step failed or was unnecessary, a new pattern emerged, a guardrail was missing, a workaround became a pattern, or a debugging session reveals a gap.
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。
Plan which model tier handles which work BEFORE execution begins — a high-cognition model deeply understands the problem, lays the foundations, then emits a modular plan assigning each module the cheapest tier that can safely execute it, with escalation tripwires and one-way-door protection. Advisory only: it announces "next module → tier X / model Y" at each boundary and the HUMAN switches models — harnesses like Cursor cannot switch mid-run. Load when the user asks which model to use, wants a model plan, model tiers, model-tier routing, assign models to tasks or modules, says "cheap model got stuck", "which model for this task", "cost-efficient model choice", or when implementation-plan / problem-to-plan need a model: tier column. NOT dynamic-routing (plan-path selection after failure) — this skill assigns cognition tiers to work.
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。
Compress bloated project or global memory while preserving decisions, rationale, revisit triggers, provenance, and active user preferences. Load when memory exceeds budget, global memory is too large, session logs are repetitive, or before appending to an over-budget memory file.
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。
Apply Boyd's OODA loop to navigate fast-moving, uncertain, or competitive situations — Observe what is actually happening, Orient through mental models and context, Decide on the clearest path, Act quickly, then loop again. Load when the situation is changing faster than the current plan, when a competitive response is needed, when the user is stuck in analysis paralysis in a dynamic environment, when shipping under uncertainty, or when deep-thinking diagnoses a fast-moving / competitive frame. Triggers on "what should we do right now", "the situation is changing", "how do we respond to this", "competitive response", "we need to move fast", or "we're stuck deciding". Based on John Boyd's OODA loop — Observe, Orient, Decide, Act — adapted for product and business contexts (OODA Canvas 2026).
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。
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。
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。
Capture durable project memory from work, debates, debugging discoveries, learned conventions, deferred options, and session outcomes. Load when the user says remember this, save this learning, record what happened, update project memory, or preserve context for future agents.
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。
Harden an application against common security risks — validate inputs at boundaries, least-privilege access, safe secrets handling, dependency hygiene, and secure defaults. Load when shipping user-facing code, adding auth/session flows, handling untrusted data, exposing APIs, or the user asks for "security hardening", "OWASP hardening", "secure this feature". Not for skill-library security gates (use secure-skill family).
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。
Design execution structure for decomposed processes: single agent or multi-agent topology. Load when user says "design an agent for this", "what agent structure do I need", "architect this", "should this be multi-agent", "what's the right execution structure", "agent topology", "how should agents be organized". Takes process-decomposer output as primary input. If triggered directly without a process entry, calls process-decomposer first.
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。
Capture the "why" behind technical choices to prevent architectural drift. Load when the user makes a major technical decision, chooses a library/framework, defines a system boundary, or changes a core architectural pattern. Also triggers on "record a decision", "write an ADR", "why did we do this", "document this architectural choice", or "architectural decision record". Supports `SYNTHESIS=true` mode for retrospective ADR backfill from observed repo state — used by `retroactive-project-setup` and any future backfill skill. Essential for long-term project maintainability and agent alignment.
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。