notes on Lumen Night Reader

Codex Pet — Technical Reference

Tue, 26 May 2026 12:36:14 +0000

Codex Pet — Technical Reference

1. What Codex Pet Is

Codex Pets are optional animated companions built into the OpenAI Codex desktop app. They render as a floating overlay that stays on top of every other window, even when Codex itself is minimized, so the agent’s activity is visible while you work in other applications.

A pet is a passive status surface with one active capability: if a pet shows a message while a task is running, clicking it opens a reply path back to the agent, turning the indicator into a small two-way channel.

Agentic Ai Ecosystem 2026 Consolidated Notes

Sun, 17 May 2026 23:22:33 +0000

Overview

The 2025–2026 agentic‑AI shift moved from simple chat‑assistants to autonomous “workers” that operate on the cycle observe → plan → act → verify → recover. Modern platforms compete not on the underlying language model but on the agent harness — sandboxing, tool execution, memory, observability, deterministic orchestration, and governance. Successful systems minimise uncontrolled autonomy while preserving useful execution power.

Methodology & Metrics

Platforms are grouped by their primary role (IDE, extensions, CLI agents, cloud agents, business platforms, browser agents, orchestrators, frameworks, open‑source agents, sensor agents, infrastructure and foundation models). Ranking within a group considers GitHub stars, installations/downloads, enterprise adoption, mentions in Q1–Q2 2026 industry reports, benchmark results, ecosystem activity, practical applicability and financial metrics. All metrics come from the original notes and require independent verification before use in reports.

Obsidian CLI

Sun, 17 May 2026 23:07:00 +0000

Title: Obsidian CLI - Obsidian Help

URL Source: https://obsidian.md/help/cli

Markdown Content: Obsidian CLI is a command line interface that lets you control Obsidian from your terminal for scripting, automation, and integration with external tools.

Anything you can do in Obsidian you can do from the command line. Obsidian CLI even includes developer commands to access developer tools, inspect elements, take screenshots, reload plugins, and more.

Install Obsidian CLI

Enable Obsidian CLI in Obsidian:

Prompt Engineering Guide Condensed

Sun, 17 May 2026 23:06:54 +0000

Prompt Engineering Guide — Condensed Reference

A concise summary of promptingguide.ai Covers core concepts, techniques, applications, risks, and best practices.

Introduction
LLM Settings
Elements of a Prompt
General Tips for Designing Prompts
Basic Task Examples
Core Prompting Techniques
Advanced Prompting Techniques
Agentic & Tool-Augmented Techniques
Risks & Misuses
Model-Specific Notes (ChatGPT)
Tools & Libraries

1. Introduction

Prompt engineering is the discipline of developing and optimizing prompts to efficiently use large language models (LLMs) for a wide variety of applications.

Skill Md Unified Strict Standard

Sun, 17 May 2026 23:06:54 +0000

SKILL.md Unified Strict Standard

Status: Normative
Version: 2.0.0
Sources synthesized: Agent Skills spec (agentskills.io), anthropics/skills, anthropics/claude-code plugin-dev, openai/skills, github/awesome-copilot, Mintlify, Skills Directory, Geeksfino/openskills, addyosmani/agent-skills
Scope: Cross-host portable core (Claude Code, Codex CLI, GitHub Copilot CLI, OpenClaw, compatible hosts)

1. Executive Summary

This document defines a single, maximally strict specification for SKILL.md bundles, synthesized from all major skill ecosystem implementations and deep-research outputs across multiple AI providers. The portable profile is intentionally narrower than the full ecosystem because the source corpus agrees on the core artifact model — directory-scoped skill, required SKILL.md, YAML frontmatter plus Markdown body, progressive disclosure, and optional bundled resources — but diverges on frontmatter breadth, host-specific runtime controls, install/discovery paths, and metadata overlays.

Stage Md Spec Driven Agent

Sun, 17 May 2026 23:06:54 +0000

Generic Markdown Stage Format for Spec-Driven AI Agent Pipelines

Suggested filename: STAGE.md

Goal

One markdown file = one self-sufficient pipeline stage.

Each stage must:

describe what it is
declare its input dependencies
declare its output contract
link to previous and next stages
be human-readable
be parseable by a minimal Python agent
work for any pipeline topology, not only requirements → design → tasks → scaffold

Core Idea

Each stage file is markdown with a YAML frontmatter header.

Git Branching Strategies

Sun, 17 May 2026 23:06:52 +0000

Git Branching Strategies

Comparison Matrix

Strategy	Branches	Release Cadence	Complexity	CI/CD Fit	Multi-version	Team Size	Best For
Trunk-Based	`main` only, short-lived branches (<1 day)	Continuous	Low	✓	✗	Any	High-velocity SaaS
GitHub Flow	`main` + `feature/*`	Continuous	Low	✓	✗	Small–Mid	SaaS, startups, OSS
GitLab Flow	`main` + `feature/*` + env branches	Continuous with gates	Medium	✓	◐	Mid	Teams needing staging gates
Ship / Show / Ask	`main` + `feature/*`	Continuous	Low	✓	✗	Small–Mid	Balancing speed with review
Stacked Diffs	`main` + dependent chain	Continuous	Medium	◐	✗	Mid–Large	Large changes, atomic reviews
Feature Flag Flow	`main` (trunk-based + flags)	Deploy ≠ Release	Medium	✓	◐	Mid–Large	Decoupling deploy from release
Release Flow	`main` + `release/*`	Scheduled	Medium	◐	✓	Large	Discrete releases, Microsoft-style
Gitflow	`main`, `develop`, `feature/`, `release/`, `hotfix/*`	Scheduled	High	◐	✓	Mid–Large	Formal QA, multiple versions

Legend: ✓ strong fit, ◐ partial, ✗ weak fit

Kimi Cli Memory Options

Sun, 17 May 2026 23:06:52 +0000

Kimi CLI Long-Term Memory Options

Consolidated, validated reference for adding durable cross-session memory to Kimi Code CLI. All claims about external repositories were re-verified against upstream sources (May 2026). Unverified or contradicted claims from source drafts are marked or removed.

Verdict

Best default (validated) → agentmemory (rohitg00)
 MCP stdio, 51 tools, local iii-engine + embeddings, REST + viewer
 Officially supports Claude Code, Cursor, Gemini CLI, OpenCode,
 Codex CLI, Hermes, OpenClaw, pi. Kimi CLI not on official list,
 but standard MCP stdio block should work.

Best minimal local → ai-memory-mcp (alphaonedev)
 Rust binary, single SQLite + FTS5, 97.8% R@5 on LongMemEval,
 26 MCP tools, WAL mode, 79% smaller TOON output, no API cost.

Best Kimi-native → kimi-mneme (claimed by source drafts) — UNVERIFIED
 ⚠️ Could not be located on GitHub or PyPI in May 2026.
 Do not include in install plan until existence confirmed.

Best minimal Python → rekal (janbjorge)
 Python 3.11+, single SQLite + FTS5 + sqlite-vec (384-dim),
 16 MCP tools, simple stdio, primary target Codex CLI / OpenCode.

Best MCP graph route → mem0-mcp-selfhosted (elvismdev)
 Qdrant + optional Neo4j + Ollama, ~11 tools, fully offline.

Best multi-agent → HeurChain
 Confirmed Kimi CLI read/write via MCP SSE in source drafts;
 Redis + vault, ACT-R decay, BM25 only.

Best temporal reasoning → Graphiti (Zep)
 Neo4j/FalkorDB, fact validity windows, NER pipeline.
 Operationally heavy; specialized use case.

Avoid → MemNexus, Mem0 Cloud, Zep Cloud (data leaves machine)
 Letta, Honcho (replace the agent rather than extend it)
 Raw vector DBs without memory logic (RAG poisoning over time)
 SSE-only servers for new setups (SSE deprecated in MCP spec March 2025)
 kimi-memory-mcp (SARPixelPioneer) — AgentSeal 75/100, DeepSeek required

Kimi CLI Native Memory Surface — What You Get Out of the Box

Feature	What it gives	What it does not give
Session persistence	Continue a session; context survives compaction via `PreCompact`/`PostCompact` hooks	Durable searchable memory across sessions or projects
`AGENTS.md`	Project rules and conventions auto-loaded on session start	Automatic extraction of decisions, debugging insights, or evolving facts
Hooks (Beta)	13 lifecycle events configured as `[[hooks]]` in `~/.kimi/config.toml` (`SessionStart`, `UserPromptSubmit`, `PreToolUse`, `PostToolUse`, `Notification`, `PreCompact`, `Stop`, etc.); regex matchers, timeouts, blocking via exit code 2	Storage or retrieval backend by itself
Skills (`.kimi/skills/`)	Prompt-injected skill instructions, scoped Project > User > Extra > Built-in	Persistent cross-session memory
MCP (`~/.kimi/mcp.json`)	Any standard MCP server via stdio or Streamable HTTP; managed with `kimi mcp` subcommand	Automatic memory unless the agent actively calls memory tools
Plugins	Local toolkits packaged via `plugin.json`; OAuth credentials can be injected via `inject` block	Long-term memory unless the plugin implements it
Agent Flow	Workflow orchestration	Not a memory layer

Key constraints:

notes on Lumen Night Reader

Codex Pet — Technical Reference

Codex Pet — Technical Reference

1. What Codex Pet Is

Agentic Ai Ecosystem 2026 Consolidated Notes

Overview

Methodology & Metrics

Obsidian CLI

Install Obsidian CLI

Prompt Engineering Guide Condensed

Prompt Engineering Guide — Condensed Reference

Table of Contents

1. Introduction

Skill Md Unified Strict Standard

SKILL.md Unified Strict Standard

1. Executive Summary

Stage Md Spec Driven Agent

Generic Markdown Stage Format for Spec-Driven AI Agent Pipelines

Goal

Core Idea

Git Branching Strategies

Git Branching Strategies

Comparison Matrix

Kimi Cli Memory Options

Kimi CLI Long-Term Memory Options

Verdict

Kimi CLI Native Memory Surface — What You Get Out of the Box