continuous-learning-v2

A learning system that watches coding-agent sessions and turns repeated useful behaviours into small pieces of reusable knowledge called instincts. It can keep those instincts for one project or share them across projects, then develop them into skills, commands, or agents.

In plain words
What is it for?
Use it to observe sessions, assign confidence to learned behaviours, review or move them between project and global libraries, and turn them into reusable add-ons.
Why use it?
It reduces the need to repeatedly explain the same working preferences and patterns, while keeping project-specific lessons from affecting unrelated projects.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/junmystery/agent-guidance-python/continuous-learning-v2
Any agent
npx skills add JunMystery/Agent-Guidance-Python --skill continuous-learning-v2
Clone the repo
git clone --depth 1 https://github.com/JunMystery/Agent-Guidance-Python

Made for: Claude Code, Codex.

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,145 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00048 $0.03145
Opus 5 $0.00024 $0.01572
Sonnet 5 $0.00010 $0.00629
Haiku 4.5 $0.00005 $0.00314

Measured 2d ago against content hash 75485ddb37e2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

continuous-learning-v2 scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

If you previously copied `observe.sh` into `~/.claude/settings.json`, remove that duplicate `PreToolUse` / `PostToolUse` block. Duplicating the plugin hook causes double execution and `${CLAUDE_PLUGIN_ROOT}` resolution e
Origin

This is a copy

86% identical to continuous-learning-v2 — 57 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/continuous-learning-v2/SKILL.md · 362 lines

How it starts

The opening of the file, as written. The whole thing — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Continuous Learning v2.1 - Instinct

-Based Architecture

An advanced learning system that turns your Claude Code sessions into reusable knowledge through atomic "instincts" - small learned behaviors with confidence scoring.

v2.1 adds project-scoped instincts — React patterns stay in your React project, Python conventions stay in your Python project, and universal patterns (like "always validate input") are shared globally.

When to Activate

  • Setting up automatic learning from Claude Code sessions
  • Configuring instinct-based behavior extraction via hooks
  • Tuning confidence thresholds for learned behaviors
  • Reviewing, exporting, or importing instinct libraries
  • Evolving instincts into full skills, commands, or agents
  • Managing project-scoped vs global instincts
  • Promoting instincts from project to global scope

What's New in v2.1

Feature v2.0 v2.1
Storage Global (~/.claude/homunculus/) Project-scoped (${XDG_DATA_HOME:-~/.local/share}/ecc-homunculus/projects/<hash>/)
Scope All instincts apply everywhere Project-scoped + global
Detection None git remote URL / repo path
Promotion N/A Project → global when seen in 2+ projects
Commands 4 (status/evolve/export/import) 6 (+promote/projects)
Cross-project Contamination risk Isolated by default

What's New in v2 (vs v1)

Feature v1 v2
Observation Stop hook (session end) PreToolUse/PostToolUse (100% reliable)
Analysis Main context Background agent (Haiku)
Granularity Full skills Atomic "instincts"
Confidence None 0.3-0.9 weighted
Evolution Direct to skill Instincts -> cluster -> skill/command/agent
Sharing None Export/import instincts

The Instinct Model

An instinct is a small learned behavior:

---
id: prefer-functional-style
trigger: "when writing new functions"
confidence: 0.7
domain: "code-style"
source: "session-observation"
scope: project
project_id: "a1b2c3d4e5f6"
project_name: "my-react-app"
---

# Prefer Functional Style

## Action
Use functional patterns over classes when appropriate.

## Evidence
- Observed 5 instances of functional pattern preference
- User corrected class-based approach to functional on 2025-01-15

Read the full file on GitHub · 362 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 362 lines · 48 tokens per session scan B 75485ddb37e2

Subscribe to this mod's changes

continuous-learning-v2 is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 3,145 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). It is 86% identical to continuous-learning-v2, differing in 57 lines, and is treated as a copy.

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