Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).
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。
hoangsonww/Claude-Code-Agent-Monitor☆ 1,0772026年10月12日 更新
Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.
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。
zhnnky329/MathModeling-skills☆ 1,0572026年9月24日 更新
Build or review source-backed descriptive, diagnostic, predictive, and prescriptive analysis for consequential decisions. Use when an agent must profile and safely prepare uploaded data, turn a real dataset or research question into a reproducible study, investigate drivers without overstating causality, validate a model, compare feasible actions under dependent uncertainty and tail risk, trace every parameter to evidence and approval, or produce an answer-first analytical report across health, business, finance, policy, engineering, operations, behavioral science, AI, or planning.
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。
limingrui679-design/high-stakes-analytics-decision-lab☆ 1,0092026年10月6日 更新
Diagnose and fix failures in a built third-party `.ppmplugin` control: crashes, silent no-ops, PCF error outputs, or incorrect behavior. Uses the reported symptom, `shared/error-codes.md`, and file-level evidence to trace the manifest, Android/iOS modules, PCF dispatch, and build configuration. Produces a ranked diagnosis, asks for approval, then applies a surgical fix while keeping the committed manifest and affected contracts synchronized. Re-validates manifest changes through /generate-ppmplugin-manifest.
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。
microsoft/power-platform-skills☆ 1,0062026年10月15日 更新
Inspects and configures the security headers a Power Pages site sends to browsers — Content Security Policy, frame and clickjacking protection, cross-origin sharing, cookie behavior, and related site settings. Identifies gaps and walks the user through fixes. Use when the user wants to review headers, fix CSP errors, allow embedding in another site, control cross-origin access, harden cookie settings, or asks "are my browser settings safe?", "fix my CSP", "set up CORS" — even if they only mention a specific header name without saying "security headers".
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。
microsoft/power-platform-skills☆ 1,0062026年10月15日 更新
Use when building gameplay systems in Godot 4.7: enemy AI that patrols, chases and attacks, state machines, behavior trees (LimboAI), NavigationAgent3D pathfinding and avoidance for 100 to 1000 enemies, 'agents stack up' or 'path is empty', hitbox and hurtbox combat, fast bullets going through walls, save and load, inventory, quests, dialogue (Dialogue Manager), input remapping, procedural dungeons, or measuring agent counts and frame time headless.
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。
scenario-labs/skills☆ 1,0052026年10月14日 更新
Use when building or debugging UE5 gameplay: a character with double jump or dash, abilities with cooldowns, enemy AI that patrols, chases and attacks, a health bar or HUD; choosing Blueprint vs C++, GAS or not, StateTree vs Behavior Tree, EQS or Mass; setting up Enhanced Input, Common UI or UMG; replication, RepNotify, save games, World Partition state; "Blueprints are slow", Tick, casts and hard references; "ability won't activate", "enemy ignores the player"; or writing automated gameplay tests with injected input.
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。
scenario-labs/skills☆ 1,0052026年10月14日 更新
Use when building or debugging Unity gameplay systems: enemy AI that patrols, chases and attacks, NavMesh baking and agents (AI Navigation 2), feet sliding on agents, state machines or behavior trees, physics projectiles that tunnel, the physics spiral, layers and the collision matrix, CharacterController vs Rigidbody characters, object pooling, 'hundreds of enemies', DOTS, Burst or Jobs decisions, Netcode for GameObjects multiplayer, audio mixers, snapshots, volume sliders and 3D combat sounds.
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。
scenario-labs/skills☆ 1,0052026年10月14日 更新
Build production-ready frontend components with accessible markup, sensible props, defined states, and tested behavior. Use this skill whenever the user wants to build a component from scratch, refactor an existing one, design a component API, or implement a UI element with proper states and accessibility. Triggers on build a component, create a button, create a modal, create a form input, component API, props design, component states, refactor component, accessible component. Also triggers when implementing UI from a design that needs to be reusable.
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。
rampstackco/claude-skills☆ 9652026年10月7日 更新
Analyze event logs, clickstreams, user paths, product funnels, retention, behavioral segments, transition graphs, step matrices, sequence patterns, and customer journeys using Retentioneering. Use when the user provides CSV, Parquet, pandas, or database event data containing user, event, and timestamp columns, or asks why users convert, churn, loop, abandon a flow, or follow particular product paths. Do not use for qualitative journey-mapping workshops or aggregate website traffic without user-level event sequences.
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。
retentioneering/retentioneering-tools☆ 9332026年10月13日 更新
Analyze a software codebase for algorithmic complexity and performance hotspots, then propose or implement safe optimizations without breaking behavior. Use when Codex is asked to scan many files, find inefficient loops, nested iteration, repeated scans, costly rendering/recomputation, N+1 queries, avoidable O(n^2) or O(n) operations, or reduce complexity such as O(n^2) to O(n log n) / O(n), while preserving tests, APIs, outputs, and maintainability.
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。
Kappaemme-git/codex-complexity-optimizer☆ 9132026年5月15日 更新
Build, measure, and evolve company culture as operational behavior, not wall posters. Use when building company values, assessing culture health, designing rituals, creating culture codes, or handling culture clashes.
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。
borghei/Claude-Skills☆ 9122026年10月7日 更新
Playbook for designing SaaS and startup products that convert, retain, and monetize — landing pages & CRO, checkout & forms, onboarding/activation, churn reduction, pricing psychology, dashboards, behavioral-science tactics, feature discipline, positioning/ICP, go-to-market, and AI-era differentiation. Use when advising on product design, UX, conversion, landing pages, checkout, onboarding, trials, pricing, retention/churn, growth, or positioning for a startup or SaaS. Distilled from product designer Richard (@richardrx). Not for use on gambling, betting, or casino products.
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。
heliocosta-dev/revenue-centric-design☆ 9042026年9月4日 更新
Migrate Terraform provider resources and data sources from Plugin SDKv2 to the Plugin Framework: muxing both plugins in one provider (terraform-plugin-mux, tf5to6server), per-resource migration workflow, SDKv2-to-Framework schema mapping (ForceNew, ValidateFunc, DiffSuppressFunc, Default, Timeouts, blocks), null-vs-zero-value behavioral traps, and state-compatibility verification. Use when converting or translating SDKv2 resources to the Framework, setting up a muxed provider server, deciding whether a resource should be migrated at all, or debugging plan diffs and state errors that appeared after a migration.
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。
hashicorp/agent-skills☆ 8962026年10月5日 更新
Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.
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。
hashicorp/agent-skills☆ 8962026年10月5日 更新
Android APK decompiler that converts DEX bytecode to readable Java source code. Use when you need to decompile APK files, analyze app logic, search for vulnerabilities, find hardcoded credentials, or understand app behavior through readable source code.
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。
BrownFineSecurity/iothackbot☆ 8622026年6月1日 更新
Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.
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。
sangrokjung/claude-forge☆ 8572026年9月3日 更新
Expert blueprint for real-time strategy games including unit selection (drag box, shift-add), command systems (move, attack, gather), pathfinding (NavigationAgent2D with RVO avoidance), fog of war (SubViewport mask shader), resource economy (gather/build loop), and AI opponents (behavior trees, utility AI). Use for base-building RTS or tactical combat games. Trigger keywords: RTS, unit_selection, command_system, fog_of_war, pathfinding_RVO, resource_economy, command_queue.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8542026年10月14日 更新
Expert blueprint for sandbox games (Minecraft, Terraria, Garry's Mod) with physics-based interactions, cellular automata, emergent gameplay, and creative tools. Use when building open-world creation games with voxels, element systems, player-created structures, or procedural worlds. Keywords voxel, sandbox, cellular automata, MultiMesh, chunk management, emergent behavior, creative mode.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8542026年10月14日 更新
Expert blueprint for sports games (FIFA, NBA 2K, Rocket League, Tony Hawk) covering physics-based ball interaction, team AI formations, contextual input, and match umpire/score authority. Broadcast framing routes to godot-camera-systems. Use when building soccer, basketball, hockey, racing sports, or arcade sports games. Keywords ball physics, magnus effect, formation AI, team tactics, contextual controls, steering behaviors.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8542026年10月14日 更新
Expert blueprint for real-time strategy games including unit selection (drag box, shift-add), command systems (move, attack, gather), pathfinding (NavigationAgent2D with RVO avoidance), fog of war (SubViewport mask shader), resource economy (gather/build loop), and AI opponents (behavior trees, utility AI). Use for base-building RTS or tactical combat games. Trigger keywords: RTS, unit_selection, command_system, fog_of_war, pathfinding_RVO, resource_economy, command_queue.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Expert blueprint for sports games (FIFA, NBA 2K, Rocket League, Tony Hawk) covering physics-based ball interaction, team AI formations, contextual input, and match umpire/score authority. Broadcast framing routes to godot-camera-systems. Use when building soccer, basketball, hockey, racing sports, or arcade sports games. Keywords ball physics, magnus effect, formation AI, team tactics, contextual controls, steering behaviors.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Expert blueprint for sandbox games (Minecraft, Terraria, Garry's Mod) with physics-based interactions, cellular automata, emergent gameplay, and creative tools. Use when building open-world creation games with voxels, element systems, player-created structures, or procedural worlds. Keywords voxel, sandbox, cellular automata, MultiMesh, chunk management, emergent behavior, creative mode.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Start (or restart) a local multi-node Temps cluster using Docker-in-Docker — one control plane + 3 worker nodes, each a privileged DinD container running its own dockerd + `temps agent`, wired with the real multi-host overlay (VXLAN, compute_cidr allocation) via `tools/dev-cluster/` in whichever checkout/worktree you run it from. Invoke when the user says "start the temps cluster", "spin up a multi-node dev cluster", "test this with multiple workers", "bring up worker nodes locally", "docker in dind cluster", or wants to verify cross-node behavior (node targeting, cluster DNS, overlay networking, node join/mTLS) that a single-node `start-temps` server cannot exercise. Distinct from `start-temps` (single-node, native binary, port-slot based) and `start-temps-ee` (single-node EE binary) — this is the only path that actually has more than one node.
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。
gotempsh/temps☆ 8432026年10月14日 更新