Finishing a Development Branch
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템.
$ npx skills add affaan-m/ECC --skill continuous-learning-v2 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install affaan-m/ECC continuous-learning-v2 --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/ko-KR/skills/continuous-learning-v2 .claude/skills/continuous-learning-v2 && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "continuous-learning-v2" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2 into .claude/skills/continuous-learning-v2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "continuous-learning-v2", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add affaan-m/ECC --skill continuous-learning-v2 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install affaan-m/ECC continuous-learning-v2 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .agents/skills && cp -r skills-src/docs/ko-KR/skills/continuous-learning-v2 .agents/skills/continuous-learning-v2 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "continuous-learning-v2" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2 into .agents/skills/continuous-learning-v2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "continuous-learning-v2", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill continuous-learning-v2 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install affaan-m/ECC continuous-learning-v2 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/docs/ko-KR/skills/continuous-learning-v2 .cursor/skills/continuous-learning-v2 && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "continuous-learning-v2" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2 into .cursor/skills/continuous-learning-v2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "continuous-learning-v2", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/affaan-m/ECC.git --path docs/ko-KR/skills/continuous-learning-v2--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add affaan-m/ECC --skill continuous-learning-v2 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install affaan-m/ECC continuous-learning-v2 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/docs/ko-KR/skills/continuous-learning-v2 .gemini/skills/continuous-learning-v2 && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "continuous-learning-v2" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2 into .gemini/skills/continuous-learning-v2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "continuous-learning-v2", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install affaan-m/ECC continuous-learning-v2Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add affaan-m/ECC --skill continuous-learning-v2 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .github/skills && cp -r skills-src/docs/ko-KR/skills/continuous-learning-v2 .github/skills/continuous-learning-v2 && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "continuous-learning-v2" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2 into .github/skills/continuous-learning-v2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "continuous-learning-v2", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill continuous-learning-v2 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install affaan-m/ECC continuous-learning-v2 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/docs/ko-KR/skills/continuous-learning-v2 .opencode/skills/continuous-learning-v2 && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "continuous-learning-v2" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/ko-KR/skills/continuous-learning-v2 into .opencode/skills/continuous-learning-v2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "continuous-learning-v2", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
continuous-learning-v2훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템.
Continuous Learning V2 is an agent skill from affaan-m/ECC. 훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템. v2.1에서는 프로젝트 간 오염을 방지하기 위한 프로젝트 범위 본능이 추가되었습니다.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development. It works with Git. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 4eb71d9. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
python3gitFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
skill-creator.appx.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Continuous Learning V2 loads about 2.3k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 795 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from affaan-m/ECC at commit 4eb71d9, republished under its MIT licence (© affaan-m). 795 words, ~2,308 tokens.
.claude/skills/continuous-learning-v2/SKILL.md (or your agent's skills folder).Claude Code 세션을 원자적 "본능(instinct)" -- 신뢰도 점수가 있는 작은 학습된 행동 -- 을 통해 재사용 가능한 지식으로 변환하는 고급 학습 시스템입니다.
v2.1에서는 프로젝트 범위 본능이 추가되었습니다 -- React 패턴은 React 프로젝트에, Python 규칙은 Python 프로젝트에 유지되며, 범용 패턴(예: "항상 입력 유효성 검사")은 전역으로 공유됩니다.
| 기능 | v2.0 | v2.1 |
|---|---|---|
| 저장소 | 전역 (~/.claude/homunculus/) | 프로젝트 범위 (projects/<hash>/) |
| 범위 | 모든 본능이 어디서나 적용 | 프로젝트 범위 + 전역 |
| 감지 | 없음 | git remote URL / 저장소 경로 |
| 승격 | 해당 없음 | 2개 이상 프로젝트에서 확인 시 프로젝트 -> 전역 |
| 명령어 | 4개 (status/evolve/export/import) | 6개 (+promote/projects) |
| 프로젝트 간 | 오염 위험 | 기본적으로 격리 |
| 기능 | v1 | v2 |
|---|---|---|
| 관찰 | Stop 훅 (세션 종료) | PreToolUse/PostToolUse (100% 신뢰성) |
| 분석 | 메인 컨텍스트 | 백그라운드 에이전트 (Haiku) |
| 세분성 | 전체 스킬 | 원자적 "본능" |
| 신뢰도 | 없음 | 0.3-0.9 가중치 |
| 진화 | 직접 스킬로 | 본능 -> 클러스터 -> 스킬/명령어/에이전트 |
| 공유 | 없음 | 본능 내보내기/가져오기 |
본능은 작은 학습된 행동입니다:
---
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 2025-01-15속성:
project (기본값) 또는 global세션 활동 (git 저장소 내)
|
| 훅이 프롬프트 + 도구 사용을 캡처 (100% 신뢰성)
| + 프로젝트 컨텍스트 감지 (git remote / 저장소 경로)
v
+---------------------------------------------+
| projects/<project-hash>/observations.jsonl |
| (프롬프트, 도구 호출, 결과, 프로젝트) |
+---------------------------------------------+
|
| 관찰자 에이전트가 읽기 (백그라운드, Haiku)
v
+---------------------------------------------+
| 패턴 감지 |
| * 사용자 수정 -> 본능 |
| * 에러 해결 -> 본능 |
| * 반복 워크플로우 -> 본능 |
| * 범위 결정: 프로젝트 또는 전역? |
+---------------------------------------------+
|
| 생성/업데이트
v
+---------------------------------------------+
| projects/<project-hash>/instincts/personal/ |
| * prefer-functional.yaml (0.7) [project] |
| * use-react-hooks.yaml (0.9) [project] |
+---------------------------------------------+
| instincts/personal/ (전역) |
| * always-validate-input.yaml (0.85) [global]|
| * grep-before-edit.yaml (0.6) [global] |
+---------------------------------------------+
|
| /evolve 클러스터링 + /promote
v
+---------------------------------------------+
| projects/<hash>/evolved/ (프로젝트 범위) |
| evolved/ (전역) |
| * commands/new-feature.md |
| * skills/testing-workflow.md |
| * agents/refactor-specialist.md |
+---------------------------------------------+시스템이 현재 프로젝트를 자동으로 감지합니다:
CLAUDE_PROJECT_DIR 환경 변수 (최우선 순위)git remote get-url origin -- 이식 가능한 프로젝트 ID를 생성하기 위해 해시됨 (서로 다른 머신에서 같은 저장소는 같은 ID를 가짐)git rev-parse --show-toplevel -- 저장소 경로를 사용한 폴백 (머신별)각 프로젝트는 12자 해시 ID를 받습니다 (예: a1b2c3d4e5f6). ~/.claude/homunculus/projects.json의 레지스트리 파일이 ID를 사람이 읽을 수 있는 이름에 매핑합니다.
~/.claude/settings.json에 추가하세요.
플러그인으로 설치한 경우 (권장):
~/.claude/settings.json에 추가 hook 블록을 넣지 마세요. Claude Code v2.1+가 플러그인의 hooks/hooks.json을 자동으로 로드하며, observe.sh는 이미 그곳에 등록되어 있습니다.
이전에 observe.sh를 ~/.claude/settings.json에 복사했다면 중복된 PreToolUse / PostToolUse 블록을 제거하세요. 중복 등록은 이중 실행과 ${CLAUDE_PLUGIN_ROOT} 해석 오류를 일으킵니다. 이 변수는 플러그인 소유 hooks/hooks.json 항목에서만 확장됩니다.
수동으로 ~/.claude/skills에 설치한 경우, 아래 내용을 ~/.claude/settings.json에 추가하세요:
{
"hooks": {
"PreToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh"
}]
}],
"PostToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh"
}]
}]
}
}시스템은 첫 사용 시 자동으로 디렉터리를 생성하지만, 수동으로도 생성할 수 있습니다:
# Global directories
mkdir -p ~/.claude/homunculus/{instincts/{personal,inherited},evolved/{agents,skills,commands},projects}
# Project directories are auto-created when the hook first runs in a git repo/instinct-status # 학습된 본능 표시 (프로젝트 + 전역)
/evolve # 관련 본능을 스킬/명령어로 클러스터링
/instinct-export # 본능을 파일로 내보내기
/instinct-import # 다른 사람의 본능 가져오기
/promote # 프로젝트 본능을 전역 범위로 승격
/projects # 모든 알려진 프로젝트와 본능 개수 목록| 명령어 | 설명 |
|---|---|
/instinct-status | 모든 본능 (프로젝트 범위 + 전역) 을 신뢰도와 함께 표시 |
/evolve | 관련 본능을 스킬/명령어로 클러스터링, 승격 제안 |
/instinct-export | 본능 내보내기 (범위/도메인으로 필터링 가능) |
/instinct-import <file> | 범위 제어와 함께 본능 가져오기 |
/promote [id] | 프로젝트 본능을 전역 범위로 승격 |
/projects | 모든 알려진 프로젝트와 본능 개수 목록 |
백그라운드 관찰자를 제어하려면 config.json을 편집하세요:
{
"version": "2.1",
"observer": {
"enabled": false,
"run_interval_minutes": 5,
"min_observations_to_analyze": 20
}
}| 키 | 기본값 | 설명 |
|---|---|---|
observer.enabled | false | 백그라운드 관찰자 에이전트 활성화 |
observer.run_interval_minutes | 5 | 관찰자가 관찰 결과를 분석하는 빈도 |
observer.min_observations_to_analyze | 20 | 분석 실행 전 최소 관찰 횟수 |
기타 동작 (관찰 캡처, 본능 임계값, 프로젝트 범위, 승격 기준)은 instinct-cli.py와 observe.sh의 코드 기본값으로 구성됩니다.
~/.claude/homunculus/
+-- identity.json # 프로필, 기술 수준
+-- projects.json # 레지스트리: 프로젝트 해시 -> 이름/경로/리모트
+-- observations.jsonl # 전역 관찰 결과 (폴백)
+-- instincts/
| +-- personal/ # 전역 자동 학습된 본능
| +-- inherited/ # 전역 가져온 본능
+-- evolved/
| +-- agents/ # 전역 생성된 에이전트
| +-- skills/ # 전역 생성된 스킬
| +-- commands/ # 전역 생성된 명령어
+-- projects/
+-- a1b2c3d4e5f6/ # 프로젝트 해시 (git remote URL에서)
| +-- observations.jsonl
| +-- observations.archive/
| +-- instincts/
| | +-- personal/ # 프로젝트별 자동 학습
| | +-- inherited/ # 프로젝트별 가져온 것
| +-- evolved/
| +-- skills/
| +-- commands/
| +-- agents/
+-- f6e5d4c3b2a1/ # 다른 프로젝트
+-- ...| 패턴 유형 | 범위 | 예시 |
|---|---|---|
| 언어/프레임워크 규칙 | project | "React hooks 사용", "Django REST 패턴 따르기" |
| 파일 구조 선호도 | project | "__tests__/에 테스트", "src/components/에 컴포넌트" |
| 코드 스타일 | project | "함수형 스타일 사용", "dataclasses 선호" |
| 에러 처리 전략 | project | "에러에 Result 타입 사용" |
| 보안 관행 | global | "사용자 입력 유효성 검사", "SQL 새니타이징" |
| 일반 모범 사례 | global | "테스트 먼저 작성", "항상 에러 처리" |
| 도구 워크플로우 선호도 | global | "편집 전 Grep", "쓰기 전 Read" |
| Git 관행 | global | "Conventional commits", "작고 집중된 커밋" |
같은 본능이 높은 신뢰도로 여러 프로젝트에 나타나면, 전역 범위로 승격할 후보가 됩니다.
자동 승격 기준:
승격 방법:
# Promote a specific instinct
python3 instinct-cli.py promote prefer-explicit-errors
# Auto-promote all qualifying instincts
python3 instinct-cli.py promote
# Preview without changes
python3 instinct-cli.py promote --dry-run/evolve 명령어도 승격 후보를 제안합니다.
신뢰도는 시간이 지남에 따라 진화합니다:
| 점수 | 의미 | 동작 |
|---|---|---|
| 0.3 | 잠정적 | 제안되지만 강제되지 않음 |
| 0.5 | 보통 | 관련 시 적용 |
| 0.7 | 강함 | 적용이 자동 승인됨 |
| 0.9 | 거의 확실 | 핵심 행동 |
신뢰도가 증가하는 경우:
신뢰도가 감소하는 경우:
"v1은 관찰에 스킬을 의존했습니다. 스킬은 확률적입니다 -- Claude의 판단에 따라 약 50-80%의 확률로 실행됩니다."
훅은 100% 확률로 결정적으로 실행됩니다. 이는 다음을 의미합니다:
v2.1은 v2.0 및 v1과 완전히 호환됩니다:
~/.claude/homunculus/instincts/의 기존 전역 본능이 전역 본능으로 계속 작동~/.claude/skills/learned/ 스킬이 계속 작동본능 기반 학습: Claude에게 당신의 패턴을 가르치기, 한 번에 하나의 프로젝트씩.
© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in docs/ko-KR/skills/continuous-learning-v2 of affaan-m/ECC.
Open the folder on GitHubat commit 4eb71d9
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.
Continuous Learning V2 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Continuous Learning V2 this skillaffaan-m/ECC | 276k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Code Design Rationale Investigatorcursor/plugins | 11k | 9 repos | ~2.6k | Automated safety check: Pass | None | |
| Contributor-First PR MergeHKUDS/OpenHarness | 16k | 1 repos | ~847 | Automated safety check: Pass | MIT | |
| Finishing A Development Branchfarm-fe/farm | 5.6k | 34 repos | ~1.8k | Automated safety check: Pass | MIT |
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
cursor/plugins
Digs into why code is shaped the way it is by checking git history, pull requests and connected tools in parallel, then reporting a cited read on the tradeoffs.
HKUDS/OpenHarness
Merges external GitHub pull requests while keeping the original author credited, and fixes conflicts after the merge instead of rewriting the contribution.
farm-fe/farm
A skill your agent uses when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for…
TryGhost/Ghost
Moves a package from another TryGhost repository into Ghost as an internal workspace package while keeping its Git history, with checkpoints for the steps that need an administrator.
affaan-m/ECC
Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.
affaan-m/ECC
Ingests, indexes, searches, edits and monitors video, audio and live streams through the VideoDB Python SDK, returning stream links, clips and timestamps.
affaan-m/ECC
Route broad documentation-governance requests to existing ECC skills and run an opt-in, read-only audit of mapped documentation roles, links, ADR indexes, and evidence references.
affaan-m/ECC
Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.
affaan-m/ECC
Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.
affaan-m/ECC
Measures whether agents actually follow a skill, rule or agent definition by generating scenarios at three strictness levels and scoring tool-call traces.
Works with
Categories
훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템. Continuous Learning V2 is an agent skill from affaan-m/ECC. 훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템.
Continuous Learning V2 fits situations like: development work in your project.
Run `npx skills add affaan-m/ECC --skill continuous-learning-v2 -a claude-code`. Or copy the skill folder (docs/ko-KR/skills/continuous-learning-v2 in affaan-m/ECC) into .claude/skills/continuous-learning-v2 in your project. Claude Code loads it when a task matches its description.
Run `npx skills add affaan-m/ECC --skill continuous-learning-v2 -a codex`. Or copy the skill folder (docs/ko-KR/skills/continuous-learning-v2 in affaan-m/ECC) into .agents/skills/continuous-learning-v2 in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill continuous-learning-v2 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/continuous-learning-v2, .gemini/skills/continuous-learning-v2, .github/skills/continuous-learning-v2 and .opencode/skills/continuous-learning-v2 in your project.
Going by SKILL.md and its folder, Continuous Learning V2 needs the command-line tools its instructions call (python3 and git). Our summary lists: Python 3.
SKILL.md names 2 domains. As links in the text: skill-creator.app and x.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Continuous Learning V2 is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Continuous Learning V2: Finishing a Development Branch (obra/superpowers, 297k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Code Design Rationale Investigator (cursor/plugins, 11k stars) and Contributor-First PR Merge (HKUDS/OpenHarness, 16k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,111 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 10, 2026.
Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.