技能 codeconscious-identity
🧠
codeconscious-identity
安全 ⚙️
外部命令🌐
網路存取📁
檔案系統存取
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.
支援: Claude Codex Code(CC)
1
下載技能 ZIP
2
在 Claude 中上傳
前往 設定 → 功能 → 技能 → 上傳技能
3
開啟並開始使用
測試它
正在使用「codeconscious-identity」。 /runtime.explore
預期結果:
- 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"
預期結果:
- 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"
預期結果:
- 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
安全審計
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.
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已掃描檔案
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分析行數
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發現項
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審計總數
風險因素
⚙️ 外部命令 (553)
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審計者: claude 查看審計歷史 →
品質評分
50
架構
100
可維護性
85
內容
21
社群
100
安全
91
規範符合性
你能建構什麼
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
試試這些提示
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"
最佳實務
- 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
常見問題
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