continuous-learning
Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.
소스 정보
- 저장소
- a5c-ai/babysitter
- 최근 소스 활동
- 2026년 6월 1일 07:46
- 감지된 SKILL.md 언어
- 영어
- 스타
- 1,832
- 포크
- 113
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
파일 탐색기
2 개 파일SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- continuous-learning
- description
- Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.
- allowed-tools
- Read, Write, Edit, Bash, Grep, Glob
- graph
- {"domains":["domain:software-engineering"],"skillAreas":["skill-area:agentic-loops","skill-area:orchestration-loop"],"workflows":["workflow:feature-development"],"topics":["topic:developer-experience"],"roles":["role:tech-lead","role:backend-engineer"]}
- Analyze code changes and implementation approaches
- Identify recurring patterns and conventions
- Extract architectural decisions with rationale
- Capture error resolution strategies
- Record tool usage patterns
- Assign initial confidence scores (0-100)
### 2. Pattern Evaluation
- Score generalizability (0-100): cross-project applicability
- Score reliability (0-100): validation frequency
- Score impact (0-100): outcome improvement
- Composite: generalizability * 0.3 + reliability * 0.4 + impact * 0.3
- Filter below confidence threshold (default: 75)
- Merge similar patterns
### 3. Skill Creation
- Convert high-confidence patterns to SKILL.md format
- Write clear instructions with phases
- Include when-to-use and when-not-to-use sections
- Add usage examples and agent references
- Follow kebab-case naming convention
### 4. Organization
- Categorize: language-specific, domain, business, meta
- Resolve naming conflicts
- Update indexes and manifests
- Create dependency graphs
### 5. Version and Export
- Assign semantic versions by maturity
- Create portable export bundles
- Include usage examples and test cases
- Generate import instructions
## Strategic Compaction
- Analyze context token usage
- Identify low-value context for compression
- Archive completed phases to memory files
- Calculate token savings per suggestion
## When to Use
- End of development sessions
- After significant code reviews
- After debugging sessions
- Periodically during long sessions
## Agents Used
- `continuous-learning` (custom agent for this skill)
- `context-engineering` (compaction analysis)
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