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One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.

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Combine React's official "You Might Not Need an Effect" guidance with this project's stricter no direct useEffect stance. Use when writing, reviewing, or refactoring React components that might reach for useEffect, derived state, event relays, reset logic, subscriptions, or client fetching.

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。

Creates or adds Convex to an app. Use for new Convex projects, npm create convex@latest, frontend setup, env vars, or the first npx convex dev run.

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 for pull-request, merge, version and release mechanics in the Syntropic137 repo, and for CI or release-pipeline failures. Trigger phrases include "open a PR", "submit my changes", "address the review comments", "Copilot left comments", "merge this PR", "push this nit straight to main", "CI is red", "the release gate failed", "smoke test broke", "why is this PR BLOCKED", "bump the version", "cut a release", "release v1.x", "write the release notes", "main -> release PR", "approve the release gate", "the release published a bad asset", "triage the open PRs", "PR backlog", "which PRs are ready to merge", "merge order", "DORA metrics", "deploy frequency", "lead time", "change failure rate", "time to restore", "why didn't the issue auto-close". Covers trunk-based `main`, the `release` branch, local gates (`just qa-ci`, `just preflight`), GitHub Actions gates, review and merge policy, and post-release verification. Do NOT use for deciding what to dispatch, running the orchestrator loop, or deciding when to deploy a beta or run a pit stop (see `orchestrating`); for whether a task belongs in a workspace or locally (see `dogfooding`); for using the `syn` CLI as an end user (see the syntropic137 plugin skills).

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Guide for defining RL environments — the Env protocol, EnvGroupBuilder, RLDataset, and custom environment creation. Use when the user asks about RL environments, reward functions, or how to define custom tasks for RL training.

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。

Set up and run the full RLHF pipeline (SFT, reward model training, RL from reward model) using the Tinker API. Use when the user wants to do RLHF, train a reward model, or run the full preference-based RL pipeline.

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。

Set up and run reinforcement learning with verifiable rewards (RLVR/GRPO) for math, code, or custom environments using the Tinker API. Use when the user wants to do RL training, GRPO, reward-based optimization, or train with verifiable rewards.

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。

Set up and run multi-turn RL training for interactive environments (terminal tasks, tool use, search/RAG, games) using the Tinker API. Use when the user wants multi-turn RL, agentic training, tool-use RL, or interactive environment training.

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。

Set up and run knowledge distillation (on-policy, off-policy, or multi-teacher) from a teacher model to a student model using the Tinker API. Use when the user wants to distill knowledge, compress models, or train a student from a teacher.

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。

Guide for using renderers — the bridge between chat-style messages and token sequences. Covers renderer setup, TrainOnWhat, vision inputs, model family matching, and custom renderers. Use when the user asks about renderers, tokenization, message formatting, or vision inputs.

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Use when the team lead points Architect at a prior agistra.dev hub path and asks it to check for or perform additional migration — trigger phrasing such as 'migrate my data from <path>', 'check what didn't get migrated', 'did we miss anything from my old hub', or 'do a completeness pass on <path>'. Walks the prior hub's full directory tree read-only, diffs it against the fixed scripted migration scope plus any existing migration report, and asks the team lead one clear question at a time about anything a scripted migration would never have discovered. Never writes or copies anything itself — every confirmed item is delegated to the existing migration primitives. Do not use for the first-run scripted migration prompt during `npm run setup` — that is unrelated, already-automated flow this skill does not replace.

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。

Weekly review partner that compounds productivity gains over time. Tracks velocity, logs friction, sets next-week targets, recognizes patterns across weeks, and feeds insights back to the audit for the next loop. Use when you want a weekly review, need to identify friction, want to see patterns, or want to update your system map. Part of the architect-system loop. Outputs to system/compounder/week-{date}.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。

Game art principles. Visual style selection, asset pipeline, animation workflow.

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。

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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。

Comprehensive fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows.

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A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

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。

Automate GitHub workflows with AI assistance. Includes PR reviews, issue triage, CI/CD integration, and Git operations. Use when automating GitHub workflows, setting up PR review automation, creating GitHub Actions, or triaging issues.

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。

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

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。

Integrate MercadoPago Checkout Pro (redirect-based) into Next.js applications with any PostgreSQL database (Supabase, AWS RDS, Neon, PlanetScale, self-hosted, Prisma, Drizzle, or raw pg). Use when the user needs to: (1) Add MercadoPago payment processing to a Next.js app, (2) Create a checkout flow with MercadoPago, (3) Set up payment webhooks for MercadoPago, (4) Build payment success/failure pages, (5) Create a shopping cart with payment integration, (6) Troubleshoot MercadoPago integration issues (auto_return errors, webhook failures, hydration mismatches, double submissions). Triggers on requests mentioning MercadoPago, Mercado Pago, payment integration with MP, Argentine/Latin American payment processing, or checkout with MercadoPago. Supports all MercadoPago countries: Argentina (ARS), Brazil (BRL), Mexico (MXN), Colombia (COP), Chile (CLP), Peru (PEN), Uruguay (UYU).

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。

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

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This skill should be used when the user asks to "set up a web server", "configure HTTP or HTTPS", "perform SNMP enumeration", "configure SMB shares", "test network services", or needs guidance on configuring and testing network services for penetration testing labs.

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。

Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. I

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。

Execute comprehensive web application security testing using Burp Suite's integrated toolset, including HTTP traffic interception and modification, request analysis and replay, automated vulnerability scanning, and manual testing workflows.

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Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access, structural bioinformatics, phylogenetics, and many other bioinformatics 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。