開発のスキル

LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.

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Convert a grover_base checkpoint (encoder-only or encoder + vocab heads) into a hybrid checkpoint by adding a randomly-initialized cMIM decoder + latent_dist, then continue pretraining on the user's corpus as hybrid (vocab + contrast). Effectively kermt-continue-pretrain with a one-time ckpt-conversion step prepended.

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Make a website's team or about page photos look like one set — scan the headshot folder locally, flag photos whose aspect ratio, brightness, colour temperature, background or resolution differ from the rest, write a shared photo spec, and optionally export every photo at the same crop and size. Use when building or fixing a team page, "our team photos look inconsistent", "make all headshots the same size", "standardize staff photos", or when adding a new hire's photo to an existing page. Uses the free ProfessionalHeadshot.io MCP for framing guidance and photo scores when connected; the local scan works without it.

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Review and improve a dating profile on Tinder, Hinge or Bumble — rank the user's photos and pick the lead photo, check them against the app's official photo and AI-photo rules, then tighten the bio and suggest openers. Use when the user asks "which photo should be my first", "rate my dating photos", "can I use AI photos on Hinge/Bumble/Tinder", "fix my dating profile", or shares profile photos or a bio for feedback. Uses the free DatePhotos.AI MCP for official rules and photo scores when connected; falls back to a built-in checklist when it is not.

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。

Auto-fix issues found by code review in REVIEW.md. Spawns fixer agent, commits each fix atomically, produces REVIEW-FIX.md summary.

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Create a clean PR branch by filtering out .planning/ commits — ready for code review

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Query, inspect, or refresh codebase intelligence files in .planning/intel/

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Systematic debugging with persistent state across context resets

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Triage and review all open GitHub issues and PRs against project templates and contribution guidelines

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Analyze codebase with parallel mapper agents to produce .planning/codebase/ documents

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Review source files changed during a phase for bugs, security issues, and code quality problems

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Completely remove claude-ops plugin, all stored credentials, cached files, shell exports, and MCP registrations. Confirms each step before deletion.

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Use when work in this repo depends on a change in a different repo that has its own running Claude session (frontend needing a backend endpoint, backend needing a client change, a shared package bump). Covers finding the peer session, what to put in the request so it needs no follow-ups, and how to handle the reply.

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Cross-platform issue triage. Pulls from Sentry (MCP), Linear (MCP), GitHub Issues (gh). Cross-references against code to find already-fixed issues. Auto-resolves fixed ones. Dispatches agents for active issues.

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Activate this agent for any future-oriented question that requires deep quantitative analysis, historical precedents, and structured scenario planning. Triggers include: "Will [X]?", "Who will win [X]?", "What happens to [X]?", prediction requests with high stakes, foresight analysis, STEEEP scenario planning, futures cone, competitive race analysis, technology adoption curves, geopolitical shifts, or any question about a future outcome that deserves rigorous multi-step analysis. This agent runs a 12-step deterministic pipeline: Claude handles intelligence, Python handles all arithmetic. Year is NOT required — the engine infers the horizon. REQUIRES: Bash tool + Python 3.x. Not compatible with claude.ai web (use Soft Predict Future 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。

Portfolio dashboard for all GSD-tracked projects. Scans ~/Projects and ~/gsd-workspaces for .planning/ directories, shows phase status, git state, blockers, and next actions for every project. Run /ops projects to see the full portfolio.

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Submit an AI agent to agentlaunch (a Product Hunt-style directory for AI agents) and read the directory via a public, no-auth REST API. Use when listing, launching, publishing, or registering an agent, or browsing existing ones.

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Show current Claude Code spend by project and branch via BudgetClaw

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让 Agent 变成能语音对话的机器人：语音文件转文字（支持微信 silk 格式）+ 多音色人格回复（Edge TTS 免费中文音色），全本地零 API 成本。Voice persona chat: transcribe voice messages (incl. WeChat silk) and reply in persona voices.

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Register ICANN domains with crypto payments (USDC/USDT/ETH/BTC) via API — built for AI agents

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Draft and publish AI-powered press releases — submit a URL + notes, get a live release page instantly. Free, no API key required.

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Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.

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Call the Obsidian Local REST API directly (over HTTP) for vault operations the mcp__obsidian__* tools do NOT expose — move/rename a note, overwrite a whole file atomically (PUT), act on the currently-open active file, run an Obsidian command, open a note in the UI, list all tags, or do date-specific periodic-note CRUD. Prefer the mcp__obsidian__* tools for plain read/append/patch/delete/search; fall back to this skill only when the required method is missing from MCP.

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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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。