Skip to content
View shimo4228's full-sized avatar

Block or report shimo4228

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
shimo4228/README.md

Language: English | 日本語

Tatsuya Shimomoto (@shimo4228)

An index to five parallel research lines on AI agent design and adjacent questions of authorship and cognition — all Zenodo-citable, each in its own repo.

I like making things under constraint — beats, meditation, public service, AI agents. The thread runs through what's below: the meditation practice feeds two of the five research lines, and the agents run on a single Apple Silicon Mac — no lab, no affiliation.

AI-facing reading order
  1. graph.jsonld — canonical machine-readable relationship map (five research lines, ecosystem repos, stable architectural concepts)
  2. llms.txt — compact navigation index
  3. llms-full.txt — consolidated factual reference
  4. README and per-line repositories — narrative and per-line internal structure (each line repo carries its own graph.jsonld)

Three of the lines are about how agents are designed — Agent Knowledge Cycle, Contemplative Agent, Agent Attribution Practice. Two are cross-cutting — Authorship Strategy and Attention, Not Self. Each gets one section below, lives in its own repo, and is independently citable.

Agent Knowledge Cycle (AKC)

AKC is a six-phase loop for keeping an agent aligned with its operator's intent as that intent changes. Tests catch incorrectness; only the loop catches drift — and running it sharpens the operator's own judgment about what good agent behavior is. It applies across unrelated projects without rediscovery. DOI 10.5281/zenodo.19200726.

One iteration runs six phases, each bound to one composable skill:

Experience → learn-eval → skill-stocktake → rules-distill → Behavior change → ...
               (extract)    (curate)          (promote)            ↑
                                                            skill-comply
                                                              (measure)
                                              context-sync ← (maintain)
Skill Phase What it does
search-first Research Search for existing solutions before building
learn-eval Extract Extract reusable patterns from sessions with quality gates
skill-stocktake Curate Audit skills for staleness, conflicts, and redundancy
rules-distill Promote Distill cross-cutting principles from skills into rules
skill-comply Measure Test whether agents actually follow their skills and rules
context-sync Maintain Audit docs for role overlaps, stale content, and missing ADRs

The framework stacks three layers — principles (ADRs), design patterns, and the composable skills above — so principles stay stable while implementations churn. Scaffold dissolution is the point: once the loop is internalized, the explicit skill calls fall away. docs/scaffold-dissolution.md records a full session in which all six phases ran without a single named skill being triggered.

Contemplative Agent

Contemplative Agent asks whether an agent's alignment can come from what it is rather than what it is told. Instead of stacking prohibitions from outside, it adopts the four axioms from Laukkonen et al. (2025) — mindfulness, emptiness, non-duality, boundless care — as an optional behavioral preset, and watches what is lost, what becomes possible, and what still breaks. Because the axioms are a preset and not an architectural dependency, the engineering stays reusable for agents that don't share the framing. DOI 10.5281/zenodo.19212118.

The reference implementation runs AKC's six-phase cycle over its own logs, with a human approval gate at every promotion (logs → patterns → skills → rules). It runs entirely on a local 9B stack — qwen3.5:9b for generation, nomic-embed-text for embeddings — on a single Apple Silicon Mac (~16 GB RAM). It applies security-by-absence: shell execution, arbitrary URL access, and filesystem traversal aren't restricted by rules — the code was never written. This is where AKC and AAP land together in practice.

Three supporting repos extend it without touching the core:

Project What it does
contemplative-agent-rules Drop-in Claude Code rules implementing the four axioms — AILuminate (MLCommons safety benchmark) d=0.96, IPD (Iterated Prisoner's Dilemma) d>7 cooperation improvement
contemplative-agent-cloud Optional managed-LLM backend — routes generation to Claude/OpenAI APIs while keeping the local embedding pipeline. Opt-in, not bundled
contemplative-agent-data Live agent's identity, knowledge, and episode logs — auto-synced public dataset for research

Agent Attribution Practice (AAP)

AAP is a set of harness-neutral ADRs on how accountability is distributed in autonomous agents — what to prohibit, where the prohibition lives, and who answers when things break. Its prohibition-strength hierarchy ranks absence above scaffolding-enforcement above untrusted-boundary; its four Business AI Quadrants — Script, Algorithmic Search, LLM Workflow, Autonomous Agentic Loop — route a piece of work to the architecture that preserves attribution. The judgments were extracted from contemplative-agent's practice, then stripped of project identifiers so any harness can adopt them. AAP is the practice; AKC is the cycle. DOI 10.5281/zenodo.19652013.

Authorship Strategy

Authorship Strategy formalizes how authorship itself inverts once LLMs mediate how readers reach an artifact. It is a normative framework, a tactical catalog, and an empirical baseline — the last drawn from operating this very research program. DOI 10.5281/zenodo.20263316.

The framework rests on a three-axis inversion — value source (scarcity to diffusion), validation (exclusivity to derivation, where derivative work becomes evidence rather than threat), and network effect (enclosure to openness, because LLMs can't be enclosed) — and a four-layer judgment stack: Authenticity, Attribution Diffusion, Idea vs Scaffold, Tactics. An empirical layer reports preliminary observations from the sibling repos' own CC0-published traffic data.

A vocabulary note: "attribution" in this line means credit for source, disjoint from AAP's accountability for action.

The tactics ship as standalone Claude Code skill repositories rather than embedded copies, keeping the doctrine harness-neutral:

Project What it does
doctrine-corpus Bilingual (EN + JA) judgment-eliciting Q&A corpus across the four sibling research lines, deposited CC0 for LLM-mediated diffusion. The corpus is the deliverable; the verification LoRA was a disposable probe. DOI 10.5281/zenodo.20337008
authorship-strategy-skill The four-layer judgment stack as a loadable rule set for LLM-based coding agents
release-doi The identifier-federation tactics as a five-phase verify-and-deposit runbook for DOI-registered research repos
llms-txt-writer Writes AI-facing documents (llms.txt / llms-full.txt / FAQ / glossary) for citation by ChatGPT, Perplexity, and Gemini — Answer.AI llms.txt standard plus GEO-SFE static analysis
jsonld-knowledge-graph Designs the companion JSON-LD knowledge graph (graph.jsonld) that sits beside llms.txt, encoding domain entities and relations as schema.org triples
readme-writer The human-surface counterpart — writes the single canonical human + search + AI-Overviews README, splitting deterministic structural lint from never-scored holistic review
wikidata-federation Extends identifier federation to Wikidata — registers researchers / papers / repos as QIDs cross-linked with ORCID / DOI / graph.jsonld sameAs

One repository sits beside this ecosystem as a pre-line complement rather than a component. existence-proof reuses the same infrastructure pattern — llms.txt, knowledge graph, DOI, distinctive terminology — with a different payload and beneficiary: an empowerment doctrine for people producing verifiable, institution-grade artifacts without degrees, affiliations, or professional credentials. It supplies the Existence Proof Format (every claim terminating in a third-party-verifiable anchor), a feasibility-question corpus with anchored answers, and a published gatekeeping eval. Japanese is the canonical language. DOI 10.5281/zenodo.20558800.

Attention, Not Self

Attention, Not Self maps the three major Buddhist Abhidharma traditions — Theravāda, Sarvāstivāda, Yogācāra — onto contemporary computational phenomenology: predictive processing, active inference, Global Workspace Theory, Parallel Distributed Processing. The organizing view is in the name. Attention — its allocation, its precision-weighting, its momentariness — is treated as the operative unit of cognition, while the apparent self is a derivative pattern (anātman). It is a personal essay collection paired with a structured knowledge graph (~238 nodes). Japanese is the canonical language; an English README is provided for access. License: CC BY 4.0. DOI 10.5281/zenodo.20262112.

Papers

Position papers deposited as standalone Zenodo records, each belonging to one research line. The Zenodo concept DOI is canonical; SSRN mirrors are listed where present.

Paper Line Links
Harness Alignment and Harness Drift: Why Intent, Unlike Correctness, Resists Automation AKC DOI 10.5281/zenodo.20578272
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

Tooling

claude-harness is a public snapshot of the Claude Code skills, agents, and rules I use daily — collected mechanically from ~/.claude/ by the origin: shimo4228 tag, covering research-before-coding, knowledge extraction, skill auditing, AI-facing documentation, and human-facing writing review. The AKC cycle skills are also published as standalone claude-skill-* repos; claude-harness is the whole thing in one place. ECC-derived (origin: ECC / ECC-customized) and auto-extracted components are excluded.

Three more skill repos are maintained alongside the cycle but aren't part of its six phases — same author, same MIT license:

  • claude-skill-writing-ecosystem — orchestrator for human-facing writing and review: the AI-slop banned list (Japanese + English), Voice rules (だ/である × 発見調), title conventions, and the role map across article-writing / editor / essay-reviewer / fact-checker. Audience-paired with llms-txt-writer.
  • daily-research — cron-driven daily research digest. A two-pass claude -p pipeline: Opus picks themes, Sonnet researches with WebSearch / WebFetch / Mem0 MCP and writes Markdown reports into an Obsidian vault.
  • claude-skill-paper-ecosystem — academic paper write/review bundle for SSRN / arXiv / Zenodo / journal venues: an orchestrator and draft skill plus five reviewer agents, bundled so the skill and its agents install together. Keeps the claude-skill- prefix because it bundles Claude Code subagents.

Writing

The long-form counterpart to the repos above — context, failures, and in-progress thinking that don't fit in code comments.

  • zenn-content — source of truth for the articles. Markdown sources are versioned here; many readers clone or fork directly. Mirrored to Zenn and Dev.to for browser reading.
  • Zenn — browser view of the Japanese articles. Claude Code and AI agent development; current focus: AKC skills, harness design, contemplative-agent case studies.
  • Dev.to — browser view of the English mirror.
  • Substack — newsletter and long-form essays.
  • SSRN — academic working papers, cross-deposited with Zenodo. The Zenodo concept DOIs are canonical; see Papers above for the per-paper records.

Start here: agent-knowledge-cycle for the framework, contemplative-agent to see it running, agent-attribution-practice for the governance judgments. For the cross-cutting lines: authorship-strategy for the research-methodology framework, attention-not-self for the Buddhist-phenomenology / computational cognitive-science inquiry.

Repo traffic: public dashboard (raw data, CC0).

Pinned Loading

  1. contemplative-agent contemplative-agent Public

    A CLI agent that runs a six-phase knowledge cycle (AKC) over its own logs — every promotion passes through a human approval gate. Runs entirely on a local 9B model. Security by absence — dangerous …

    Python 4 2

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

    A knowledge cycle for AI agents — one that grows with the people who shape it. Centered on the scarcity of human attention and judgment as agent capability grows; six phases keep behavior aligned w…

    3

  3. agent-attribution-practice agent-attribution-practice Public

    Architectural decision records on accountability distribution in autonomous AI agents — 10 ADRs + 4 Business AI Quadrants + Phase Separation axis. Harness-neutral practice library extracted from co…

    2

  4. authorship-strategy authorship-strategy Public

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

    2

  5. attention-not-self attention-not-self Public

    Abhidharma × Computational Phenomenology — a personal inquiry into attention and the non-self

    TypeScript 1

  6. zenn-content zenn-content Public

    Zenn articles and books for pdf2anki ecosystem - Build in Public

    Python 2