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.
npx agentmods add commands/fusengine/agents/deep-code-analysisgit clone --depth 1 https://github.com/fusengine/agentsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00028 | $0.00500 |
| Opus 5 | $0.00014 | $0.00250 |
| Sonnet 5 | $0.00006 | $0.00100 |
| Haiku 4.5 | $0.00003 | $0.00050 |
Grade A, and why
deep-code-analysis scanned grade A with 0 findings 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 yesterday.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Deep Code Analysis
Perform comprehensive codebase investigation:
-
Initial Exploration:
Use explore-codebase to map the project structure and identify key components
Wait for exploration results.
-
Documentation Research:
Use research-expert to find official documentation for [detected frameworks/libraries]
Focus on:
- Architecture patterns used
- Best practices for detected tech stack
- Common pitfalls to avoid
-
Pattern Analysis:
- Identify design patterns (MVC, Repository, Factory, etc.)
- Analyze data flow and state management
- Map component relationships
- Detect code smells and anti-patterns
-
Security Review:
- Check for common vulnerabilities (SQL injection, XSS, CSRF)
- Validate input sanitization
- Review authentication/authorization
- Analyze dependency security
-
Performance Assessment:
- Identify N+1 query problems
- Check for memory leaks
- Analyze algorithm efficiency
- Review caching strategies
-
Generate Report:
## 🔍 Deep Code Analysis: [Project Name] ### Architecture Overview - **Pattern**: [Detected pattern] - **Tech Stack**: [Technologies] - **Structure**: [Organization approach] ### Strengths - ✅ [Positive aspect 1] - ✅ [Positive aspect 2] ### Areas for Improvement - ⚠️ [Issue 1]: [Impact] → [Recommendation] - ⚠️ [Issue 2]: [Impact] → [Recommendation] ### Security Findings - 🔒 [Finding 1] - 🔒 [Finding 2] ### Performance Opportunities - ⚡ [Optimization 1] - ⚡ [Optimization 2] ### Recommendations 1. **[Priority 1]**: [Action] 2. **[Priority 2]**: [Action]
Arguments:
- $ARGUMENTS specifies focus area (security/performance/architecture)
Example Usage:
/deep-code-analysis security→ Focus on security review/deep-code-analysis→ Comprehensive analysis
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.
- yesterday First seen · 76 lines · 28 tokens per session scan A ac2e42081e16
deep-code-analysis is a command published in the GitHub repository fusengine/agents (25 stars, last pushed 28d ago), licensed MIT. It adds 28 tokens to every session and 500 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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