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MCP ThesaurusMCP Thesaurus

エージェントスキル

エージェントスキルは、エージェントが必要に応じて読み込む指示・スクリプト・リソースのフォルダーです。MCP サーバーと違って独自のプロセスを走らせないため、コンテキスト面で軽く、監査も簡単です。

Doc Coauthoring

anthropics

コミュニティ

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or

2026年8月21日Development
ローカルサービス63/100173k

Template Skill

anthropics

コミュニティ

Replace with description of the skill and when Claude should use it.

2026年8月21日AI ML
ローカルサービス38/100173k

Smart Explore

thedotmack

コミュニティ

Token-optimized structural code search using tree-sitter AST parsing. Use instead of reading full files when you need to understand code structure, find functions, or explore a codebase efficiently.

2026年9月1日AI ML
ローカルサービス79/10093k

Mem Search

thedotmack

コミュニティ

This skill should be used when the user asks to "search memory", "what do you remember about X", "check claude-mem", "mem search", "find past observations", "what did we do last session", or wants prior-session context about a project, decision, file, or task. Searches the user's Claude-Mem (cmem.ai) memory.

2026年9月1日Web Search
ローカルサービス74/10093k

How It Works

thedotmack

コミュニティ

Explain how claude-mem captures observations, when memory injection kicks in, and where data lives. Use when the user asks "how does claude-mem work?" or "what is this thing doing?".

2026年9月1日AI ML
ローカルサービス62/10093k

Ulw Research

code-yeongyu

コミュニティ

Team-first maximum-saturation research orchestration. ALWAYS asks which final format to render (PDF+DOCX default), then stands up a max-size cooperating team (team_create): one member per axis plus skeptic/red-team members for ultradebate/hyperdebate cross-critique, explore/librarian lanes, live journaling, an EXPAND loop until leads run dry, claims proven by code or the claim-graph gate, and a ci

2026年9月1日Development
ローカルサービス77/10069k

Git Master

code-yeongyu

コミュニティ

MUST USE whenever a task needs a commit or git-history investigation. Covers atomic commits, staging, commit-message style, rebase, squash, fixup/autosquash, blame, bisect, reflog, git log -S/-G, and questions like who wrote this or when was this added. Do not use for ordinary code edits unless the user asks for git work.

2026年9月1日Version Control
ローカルサービス77/10069k

Hyperplan

code-yeongyu

コミュニティ

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of

2026年9月1日Development
ローカルサービス73/10069k

Onboarding

code-yeongyu

コミュニティ

Onboarding tour for first-time omo users

2026年9月1日Development
ローカルサービス66/10069k
コミュニティ

Implement saga patterns for distributed transactions and cross-aggregate workflows. Use this skill when implementing distributed transactions across microservices where 2PC is unavailable, designing compensating actions for failed order workflows that span inventory, payment, and shipping services, building event-driven saga coordinators for travel booking systems that must roll back hotel, flight

2026年9月1日Development
ローカルサービス79/10039k
コミュニティ

Master React, Vue, and Svelte component patterns including CSS-in-JS, composition strategies, and reusable component architecture. Use when building UI component libraries, designing component APIs, or implementing frontend design systems.

2026年9月1日Design
ローカルサービス78/10039k

Histolab

K-Dense-AI

コミュニティ

Lightweight WSI tile extraction and preprocessing. Use for basic slide processing, tissue detection, tile extraction, and stain normalization for H&E images. Best for simple pipelines, dataset preparation, and quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

2026年8月31日Healthcare
ローカルサービス80/10041k

Nextflow

K-Dense-AI

コミュニティ

Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. Use whenever the user mentions Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets, or wants to run a community pipeline (e.g. nf-core/rnaseq, nf-core/sarek), write or test a module/subworkflow with nf-test, configure executors/containers (Docker, Singularity/Apptainer, Conda

2026年8月31日Development
ローカルサービス80/10041k
コミュニティ

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.

2026年9月1日Development
ローカルサービス74/10039k

Tiledbvcf

K-Dense-AI

コミュニティ

Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.

2026年8月31日File Systems
ローカルサービス76/10041k
コミュニティ

Map identified threats to appropriate security controls and mitigations. Use when prioritizing security investments, creating remediation plans, or validating control effectiveness.

2026年9月1日Development
ローカルサービス73/10039k
コミュニティ

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. O

2026年8月31日File Systems
ローカルサービス77/10027k
コミュニティ

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; agent instructions read selected project planning context when invoked. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-fram

2026年8月31日File Systems
ローカルサービス77/10027k
コミュニティ

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Gemini lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed exce

2026年8月31日File Systems
ローカルサービス77/10027k

Beads

gastownhall

コミュニティ

Use when working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.

2026年9月1日Development
ローカルサービス71/10027k

Snowflake Development

alirezarezvani

コミュニティ

Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowflake, or troubleshooting Snowflake errors.

2026年8月30日Databases
ローカルサービス77/10025k

Loop Library

alirezarezvani

コミュニティ

Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring ag

2026年8月30日AI ML
ローカルサービス77/10025k
コミュニティ

Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use when prioritizing features, synthesizing user research, writing requirement documentation, or developing product strategy.

2026年8月30日AI ML
ローカルサービス77/10025k
コミュニティ

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Kiro skill instructions and steering state read selected project planning context. Recovery reads project planning files and their timestamps only, not agent transcript stores. This adapter registers no Stop hook, never requests continuation, and never runs commands declared in Ma

2026年8月31日File Systems
ローカルサービス71/10027k