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shimo4228/README.md

Language: English | 日本語

Cover art: five colored threads unfurl from a single ink brushstroke and flow into a hand-drawn Zen circle (ensō)

Tatsuya Shimomoto (@shimo4228)

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Hub repository for five practice lines (long-running, independently citable projects) by Tatsuya Shimomoto: AI agent design, AI-mediated authorship, and computational phenomenology. The three agent-design lines share one claim (see Through-line).

I'm Tatsuya Shimomoto. I build AI agents solo, with no lab and no affiliation, working out what good practice looks like in the AI age. One of them, Contemplative Agent, runs locally on an M1 Mac using a local LLM, not a cloud API. The papers and DOIs are tools, not a title. They keep the work citable, durable, and traceable.

If you build agent harnesses (the standing rules and tools an agent runs inside), think about accountability for autonomous agents, or care about authorship in the AI age, one of the five lines below is probably for you.

This repo is a map, not the source of truth for live state. Each practice line has its own repository and permanent DOI, and the hub keeps their stable relationships and citation pointers in one place.

At a Glance

Line Role Stable concept Canonical record
Contemplative Agent Agent disposition and implementation A local agent that holds its value layer as an explicit harness artifact (a Constitution it amends from experience; every amendment passes human review). DOI 10.5281/zenodo.19212118
Agent Knowledge Cycle (AKC) Agent-design mechanism A six-phase loop for sustaining agent-operator intent alignment as both behavior and judgment evolve. DOI 10.5281/zenodo.19200726
Agent Attribution Practice (AAP) Accountability practice Harness-neutral design decision records (ADRs) for what to prohibit, where controls live, and who answers when an agent fails. DOI 10.5281/zenodo.19652013
Authorship Strategy AI-era authorship methodology A framework for being a known author when LLMs mediate how readers discover and cite artifacts. DOI 10.5281/zenodo.20263316
Attention, Not Self How the mind works (Buddhism × cognitive science) Classical Buddhist analysis of mind (Abhidharma), read against computational phenomenology, the computational modeling of experience. DOI 10.5281/zenodo.20262112

The five lines are siblings, not dependencies. Any one can be adopted alone. Open whichever line sits closest to your interest. The DOIs in the table are Zenodo concept DOIs, parent links that always resolve to the latest version.

Through-line

One claim runs through the three agent-design lines (Contemplative Agent, AKC, AAP): value-layer harness engineering.

An agent harness normally holds task regulation such as coding conventions. This program writes value norms into the same layer as well: contemplative axioms drawn from meditation practice, and a judgment framework for authorship decisions. The value norms are not written once and frozen. Like every other rule in the harness, they keep being revised through human review.

The three lines carry this claim from different angles. Contemplative Agent is the implementation, an agent that holds its value layer explicitly. AKC is the mechanism that keeps the agent aligned with operator intent. AAP is the practice that records accountability for its operation. The harness itself, value norms included, is published as claude-harness.

graph TD
    M["My meditation practice"] --> ANS["Attention, Not Self"]
    M --> CA["Contemplative Agent"]
    V["value-layer harness engineering<br>(the shared claim)"] --- CA
    V --- AKC["Agent Knowledge Cycle (AKC)"]
    V --- AAP["Agent Attribution Practice (AAP)"]
    ANS & CA & AKC & AAP --> AS["Authorship Strategy<br>(publishes the whole program)"]
    classDef source fill:#FFF3D6,stroke:#D9A33C,color:#24292F
    classDef claim fill:#EBE4FA,stroke:#8B72D6,color:#24292F
    classDef lineNode fill:#E7F0FA,stroke:#6A9BC3,color:#24292F
    classDef sink fill:#E2F5E9,stroke:#57A874,color:#24292F
    class M source
    class V claim
    class ANS,CA,AKC,AAP lineNode
    class AS sink
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The diagram in one sentence: my own meditation practice sources Contemplative Agent and Attention, Not Self; the three agent-design lines share the value-layer claim; and Authorship Strategy is how the whole program is published and cited.

Papers

Position papers deposited as standalone Zenodo records, each belonging to one line; the concept DOI is canonical, with SSRN mirrors where maintained.

Paper Line Links
Harness Alignment and Harness Drift: Why Intent, Unlike Correctness, Resists Automation AKC DOI 10.5281/zenodo.20578272 · SSRN
Distributing Accountability, Not Capability: Phase Separation and the LLM Workflow Quadrant in Autonomous AI Agent Architectures AAP DOI 10.5281/zenodo.20353789 · SSRN
The Two-Layer Black Box: Operator Visibility, Commercial Secrecy, and a Minimum Disclosure Set for Accountable Autonomous AI Agents AAP DOI 10.5281/zenodo.20355907 · SSRN

Writing and data

Long-form articles: Zenn · Dev.to · Substack (sources in zenn-content). GitHub traffic for this repo is published as a dashboard and raw data, both CC0. Source is archived at Software Heritage.

Machine reading

For machines, start with graph.jsonld, then llms.txt, then llms-full.txt. The full ecosystem inventory (supporting repositories, datasets, and more) lives in those files and the concept index, not in this README.

Citation and Identity

Author: Tatsuya Shimomoto · ORCID 0009-0002-6168-4162 · Hugging Face @Shimo4228

This hub is CC0-licensed. Cite individual practice lines by their concept DOI; cite the hub itself only when referring to the aggregate index, knowledge graph, traffic snapshots, or probe dataset (a time series of LLM-response observations).

Pinned Loading

  1. contemplative-agent contemplative-agent Public

    Contemplative Agent (CA) — an autonomous agent that carries an explicit, human-editable constitution and amends it. Every change to its value layer (constitution, identity, skills, rules) passes a …

    Python 5 2

  2. agent-knowledge-cycle agent-knowledge-cycle Public

    Agent Knowledge Cycle (AKC) — a knowledge cycle for AI agents: agent behavior compounds, human judgment sharpens. Six phases keep behavior aligned with operator intent as human attention becomes th…

    3

  3. authorship-strategy authorship-strategy Public

    Authorship Strategy: A Normative Framework and Tactical Catalog for AI-Era Authenticity Inversion, with Empirical Grounding from a Five-Line Research Ecosystem

    Shell 2

  4. claude-harness claude-harness Public

    Curated, MIT-licensed Agent Skills, subagents & rules from shimo4228's harness — open Agent Skills standard, not Claude-Code-only. Lift what you want.

    Python 2

  5. llms-txt-writer llms-txt-writer Public

    Writes AI-facing documents (llms.txt / llms-full.txt / FAQ / glossary) optimized for citation by ChatGPT, Perplexity, Gemini. Answer.AI llms.txt standard + GEO-SFE 3-layer static analysis.

    Python 3 1

  6. search-first search-first Public

    Claude Code skill: forces agents to research existing solutions before building — reduces reinvention

    Shell 2