📍 Tokyo, Japan · 🤖 NLP Engineer · 🔧 AI Agents & Harness Engineering
I’m an NLP Engineer with a background in natural language processing, knowledge graphs, and LLM applications.
More recently, I’ve been exploring AI Agents and Harness Engineering, building tools, interfaces, and workflows that make agents easier to steer, inspect, and use in real-world tasks.
My current interests include agentic workflows, developer tooling, human-in-the-loop systems, and building practical agent applications.
-
🔍 dsh-revdiff: Interactive Git diff review inside DeepSeek Harness, with structured annotations sent directly back to the current Agent session.
-
🎛️ dsh-prompt-profile: Reusable Markdown prompt profiles with per-turn model selection, argument substitution, and automatic state restoration.
-
🎯 dsh-annotate: Visual browser feedback for DeepSeek Harness. Select UI elements in Chrome and send DOM, styles, accessibility data, comments, and screenshots directly to the Agent.
-
✍️ ja-ai-polish — An Agent Skill for writing natural Japanese and reducing templated AI-writing patterns while preserving facts, voice, and intent.
-
🔎 jp-stopword-filter — A lightweight Python library for filtering Japanese stopwords with customizable rules for NLP preprocessing.
- 🤖 AI Agents
- 🔧 Agent Harnesses & Developer Tooling
- 🔄 Human-in-the-loop Agent Workflows
- 🧩 Agent UX & Tool Interfaces
- 🧠 LLM & NLP Applications
- 📝 Japanese Language Processing
I'm especially interested in the layer around the model: how agents use tools, receive feedback, manage workflows, and interact with humans.
Before my recent work on AI Agents and Harness Engineering, much of my open-source work focused on Natural Language Processing, Knowledge Graphs, and Python.
Some projects from that period:
-
📚 pydata-notebook — Chinese translation notes and examples for Python for Data Analysis.
-
🕸️ knowledge-graph-learning — A curated collection of knowledge graph tutorials, projects, papers, and communities.
-
🧠 nlp-beginner-guide-keras — NLP model implementations with Keras for beginners.
That NLP background continues to influence how I think about language models, context, structured information, and agent systems.
Building at the intersection of:
AI Agents × Harness Engineering × Developer Tools × NLP
I like turning emerging agent ideas into small, practical tools and learning what actually works by building them.
If you're also experimenting with agents, harnesses, NLP, or developer tooling, feel free to explore the repos or open an issue.