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Manage durable global/project memory in `.opc/memory/global.md` and `.opc/memory/projects/<current_project_id>.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。

Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.

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。

Build production React Native apps with Expo, navigation, native modules, offline sync, and cross-platform patterns. Use when developing mobile apps, implementing native integrations, or architecting React Native projects.

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。

Developer Experience specialist. Improves tooling, setup, and workflows. Use PROACTIVELY when setting up new projects, after team feedback, or when development friction is noticed.

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You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create acti

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Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.

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。

You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create acti

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。

Review candidate learnings in Claude Code's native auto memory (`~/.claude/projects/<project>/memory/`, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format. Majority vote (3+ of 5) promotes the entry to MEMORY.md. Use when user says "promote memory", "review my learnings", "what should graduate to MEMORY.md", "five-critic council", or as monthly memory maintenance.

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End-to-end Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.

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 someone asks to audit their AIOS, score the Four Cs, find stale paths or unlinked projects, compare AGENTS.md and CLAUDE.md, check Claude/Codex skill compatibility, or assess migration readiness. Automatically saves dated reports and tracks evidence-backed improvements across runs.

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 Codex feels slow or bloated, when local sessions/logs/worktrees/config have grown over time, or when a user wants safe maintenance for Codex Desktop/CLI state. Provides a read-only report by default, backs up before applying changes, archives instead of deleting, normalizes Windows extended paths, prunes dead config projects, rotates large logs, and moves stale worktrees.

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Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

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Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

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。

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

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Modify living Roblox Studio projects safely: inspect Explorer and execution locations, preserve existing structure, reuse modules/remotes, create meaningful Instances, apply Attributes and CollectionService tags, test server/client and multiple devices, inspect Output, and remove experiments/debug objects. Use when an agent edits a place or rbxl/rbxlx/Rojo project, operates in Studio, adds Scripts/LocalScripts/ModuleScripts, or must verify a Roblox change in context.

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Ships pull requests to open-source projects you don't maintain — CONTRIBUTING compliance, PR-size/scope checks, minimal-diff implementation, AI-disclosure PR descriptions, and rebase or bot-review replies. Use for 提 PR / 上游 PR / 贡献代码, "open a PR", "fix this upstream", "rebase against main", "respond to the bot review". Not for reviewing PRs as maintainer (use github-review-pr) or general GitHub CRUD (use github-ops).

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Spot a bad client before you sign — the warning signs of the projects that turn into unpaid, scope-creeping nightmares, and how to screen, price, or decline them. Use when asked is this client a red flag, should I take this client, screening a difficult client, or how to avoid bad clients. Produces a read on the warning signs present (haggling, vagueness, disrespect, urgency, unrealistic expectations), what each predicts, screening questions to ask before committing, protective terms if you proceed anyway, and how to decline gracefully — so you avoid the clients who cost more than they pay.

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。

Map where you are against the next level and build a concrete plan to close the gap. Use when asked to map a career ladder, find the gap to the next level, build a development/growth plan, or figure out what to work on to get promoted. Produces a level-gap map — current vs. target competencies side by side, the specific gaps, and a prioritised 1–2 quarter plan of evidence-generating projects to close them.

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Design the archive layer that keeps current workspaces lean without losing history — what moves, when, to where, findable-by-search, with the project-close ritual that makes archiving automatic instead of aspirational. Use when asked set up an archiving system, our workspace is drowning in old projects, when should things get archived, or make history findable without cluttering today. Produces the archive triggers, the destination structure, the findability rules, and the close-out ritual.

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Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?"

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Analyze KiCad projects and PDF schematics: schematics, PCB layouts, Gerbers, footprints, symbols, netlists, and design rules. Reviews designs for bugs, traces nets, cross-references schematic to PCB, extracts BOM data, checks DRC/ERC, DFM, power trees, and regulator circuits. Every finding carries a confidence label and evidence source with trust_summary rollup. Analyzes PDF schematics from dev boards, reference designs, eval kits, and datasheets. Supports KiCad 5–10. Use whenever the user mentions .kicad_sch, .kicad_pcb, .kicad_pro, PCB design review, schematic analysis, PDF schematics, reference designs, Gerber files, DRC/ERC, netlist issues, BOM extraction, signal tracing, power budget, DFM, or wants to understand, debug, compare, or review any hardware design. Also for "check my board", "review before fab", "what's wrong with my schematic", "is this ready to order", "check my power supply", "verify this circuit", OSHWA certification readiness, or any electronics/PCB design question.

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BOM (Bill of Materials) management for electronics projects — the workflow skill that coordinates DigiKey, Mouser, LCSC, element14, JLCPCB, PCBWay, and KiCad skills around a unified BOM lifecycle. Create, update, and maintain BOMs with part numbers, costs, quantities stored as KiCad symbol properties. ALWAYS trigger this skill for any task involving component sourcing, pricing, ordering, distributor searches, BOM export, or fabrication preparation — even if the user names a specific distributor or fab house (e.g. "search DigiKey for...", "generate JLCPCB BOM", "order from Mouser"). This skill analyzes the schematic for sourcing gaps, recommends which distributor/fab skills to call for each gap, and writes results back as symbol properties — the agent (or user) performs the actual searches via the called skills. Also trigger on phrases like "what parts do I need", "order components", "how much will this cost", "export for JLCPCB", "find parts for this board", "compare pricing", or "check stock".

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。

Pre-launch and pre-commit audit for vibe coding projects. Use when asked to check whether a project is ready to ship, deploy, merge, or commit, especially for common AI-built app mistakes: broken project structure, committed secrets or cache files, environment variable hygiene, database migrations, ORM/schema drift, unsafe raw SQL, unused legacy code, dead routes/components, weak auth, missing tests, build failures, and deployment footguns.

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 PostHog analytics: your user, projects, saved insights. Trigger phrases: posthog, analytics, posthog insights.

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。