技能 codeconscious-identity
🧠
codeconscious-identity
安全 ⚙️
外部命令🌐
网络访问📁
文件系统访问
Explore codebases with persistent memory
Understanding large codebases requires time and effort. CodeConscious provides an autonomous cognitive assistant that builds persistent memory across sessions, enabling deep code exploration, pattern recognition, and continuous learning from project history.
支持: Claude Codex Code(CC)
1
下载技能 ZIP
2
在 Claude 中上传
前往 设置 → 功能 → 技能 → 上传技能
3
开启并开始使用
测试它
正在使用“codeconscious-identity”。 /runtime.explore
预期结果:
- Technology stack: Node.js + Express + PostgreSQL + Redis
- Architecture pattern: Layered architecture (API → Service → Repository)
- Key modules: auth/service.js (centrality 0.85), user/repository.js (0.78)
- Dependencies: 47 files, 132 relationships identified
- Recommendations: Add tests for auth/service.js, refactor utils/helpers.js
正在使用“codeconscious-identity”。 /runtime.think "Why is the payment service slow"
预期结果:
- Analysis of payment service latency: 3 hypotheses identified
- Hypothesis 1: Database connection pool exhaustion (confidence 0.75)
- Hypothesis 2: Missing Redis cache layer for frequently accessed data (confidence 0.70)
- Hypothesis 3: Synchronous logging blocking async operations (confidence 0.60)
- Recommended: Check connection pool configuration first
正在使用“codeconscious-identity”。 /runtime.learn "Docker container security best practices"
预期结果:
- Learning complete with confidence 0.92
- Key patterns identified: minimal base images, non-root users, read-only filesystems
- Memory updated: security patterns for container deployment
- Sources reviewed: 8 documentation pages, 3 security guides
安全审计
安全v5 • 1/17/2026
Pure documentation skill containing only markdown files defining AI command behaviors. All 651 static findings are FALSE POSITIVES because: (1) files are markdown documentation, not executable code; (2) bash command examples in docs are not vulnerabilities; (3) SHA-256 hash fields are secure, not weak algorithms; (4) path examples in docs are not path traversal; (5) documentation links are legitimate. No actual code execution, network calls, filesystem access, or credential handling exists.
16
已扫描文件
6,351
分析行数
3
发现项
5
审计总数
风险因素
⚙️ 外部命令 (553)
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审计者: claude 查看审计历史 →
质量评分
50
架构
100
可维护性
85
内容
26
社区
100
安全
91
规范符合性
你能构建什么
Understand large codebases
Explore new projects quickly by building cognitive maps and dependency graphs automatically
Maintain project knowledge
Preserve architectural decisions and patterns in persistent memory across team members
Build cognitive AI agents
Implement autonomous learning agents with confidence tracking and memory systems
试试这些提示
Explore new project
/runtime.explore - scan this codebase, identify technology stack, architecture patterns, and key modules
Analyze root cause
/runtime.learn "why does the payment service timeout under load" - explore code, check logs, find root cause
Plan feature
/runtime.plan "implement OAuth2.0 authentication with JWT tokens" - break down into tasks with dependencies
Remember decision
/runtime.remember "we decided to use PostgreSQL for all new projects because of its JSON support"
最佳实践
- Use /runtime.explore first when working with unfamiliar codebases to build context
- Always use /runtime.learn before planning to understand existing architecture
- Mark confidence levels explicitly for all recommendations and findings
- Record architectural decisions with /runtime.remember for future team reference
避免
- Starting implementation without exploring or learning the codebase first
- Skipping confidence annotations on architectural recommendations
- Forgetting to record important decisions that affect future development
- Making changes without checking existing patterns in memory
常见问题
Which AI tools support this skill?
CodeConscious works with Claude, Codex, and Claude Code through standardized /runtime.* commands
How does persistent memory work across sessions?
Memory is stored in markdown files organized by type: short-term, long-term, and episodic
What confidence levels should I use?
Use above 0.90 for high confidence, 0.70-0.89 for medium, and below 0.70 for uncertain findings
Can I customize the command behaviors?
Yes, extend the markdown commands in the commands directory to customize runtime behavior
How secure is the memory system?
Memory is stored locally in markdown files within the project directory with no network access
How is this different from standard AI assistants?
CodeConscious emphasizes cognitive autonomy, persistent memory, and explicit reasoning with confidence