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.
git clone --depth 1 https://github.com/dansasser/claude-code-marketplaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/dansasser/claude-code-marketplace/deep-analyze)<a href="https://agentmods.dev/commands/dansasser/claude-code-marketplace/deep-analyze"><img src="https://agentmods.dev/badge/commands/dansasser/claude-code-marketplace/deep-analyze/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/dansasser/claude-code-marketplace/deep-analyze"><img src="https://agentmods.dev/badge/commands/dansasser/claude-code-marketplace/deep-analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00000 | $0.01434 |
| Opus 5.5 | $0.00000 | $0.00574 |
| Sonnet 5.5 | $0.00000 | $0.00287 |
| Haiku 4.5 | $0.00000 | $0.00143 |
Grade A, and why
deep-analyze 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 2mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Multi-Perspective Analysis
Comprehensive analysis using parallel orchestrator with multiple perspectives.
Usage: /deep-analyze <file_or_directory> [perspectives]
Perspectives: (comma-separated, max 4)
security: Security vulnerabilities and threat modelingarchitecture: Design patterns and structural analysisimplementation: Code quality and best practicestesting: Test coverage and validation strategiesperformance: Bottlenecks and optimization opportunities
Examples:
/deep-analyze implementation-plan.md- Auto-select perspectives/deep-analyze src/auth.py security,testing- Focus on security and testing/deep-analyze src/ architecture,security- Directory analysis with multiple perspectives/deep-analyze src/api/ security,performance- API directory deep analysis
You are performing deep multi-perspective analysis using the parallel orchestrator agent.
Target: $1 Perspectives: ${2:-auto}
Your Process:
-
Validate Target:
- Verify file/directory exists (use Read/Glob tools)
- Check size and estimate tokens
- Ensure suitable for deep analysis (not trivial files)
-
Determine Perspectives:
Auto-Select (if perspectives=$ARGUMENTS or empty): Based on file type:
- Code files (.py, .js, .ts, etc.): security, quality, testing
- Architecture docs: architecture, scalability, security
- Implementation plans: security, architecture, implementation
- API specs: security, architecture, performance
User-Specified: Parse comma-separated list from $2 Validate 2-4 perspectives
-
Invoke Parallel Orchestrator Agent:
Use Task tool to invoke ollama-parallel-orchestrator:
- Target file: $1
- Perspectives: Parsed list (2-4 perspectives)
- Agent will:
- Decompose into parallel analyses
- Execute concurrently
- Track sessions
- Synthesize results
-
Directory Operations by Perspective:
Each perspective uses optimal directory operations:
Perspective Primary Operation Example security @./dir/:search:PATTERN@./src/:search:eval,@./src/:search:passwordarchitecture @./dir/:tree@./src/:treeimplementation @./dir/:search:TODO@./src/:search:TODO,@./src/:search:FIXMEtesting @./tests/:tree@./tests/:tree,@./src/:search:testperformance @./dir/:search:PATTERN@./src/:search:for.*in,@./src/:search:query -
Perspectives Explained:
Security:
- Vulnerabilities and attack vectors
- Threat modeling
- Authentication/authorization
- Input validation
- Secrets management
- Directory ops:
@./src/:search:eval,@./src/:search:password,@./src/:search:secret
Architecture:
- Design patterns
- Structural organization
- Separation of concerns
- Modularity and coupling
- Scalability considerations
- Directory ops:
@./src/:tree,@./src/:search:import
Implementation:
- Code quality and readability
- Best practices adherence
- Error handling
- Edge case coverage
- Refactoring opportunities
- Directory ops:
@./src/:search:TODO,@./src/:search:FIXME,@./src/:tree
Testing:
- Test coverage assessment
- Testing strategy
- Edge cases and corner cases
- Integration points
- Test quality
- Directory ops:
@./tests/:tree,@./src/:search:@pytest
Performance:
- Bottleneck identification
- Algorithm efficiency
- Resource utilization
- Caching opportunities
- Optimization recommendations
- Directory ops:
@./src/:search:for.*range,@./src/:search:while,@./src/:search:query
-
Your Role:
- Invoke ollama-parallel-orchestrator agent via Task tool
- Receive comprehensive synthesized analysis
- Format report for user
- Highlight critical findings
- Present prioritized recommendations
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.
- 2mo ago First seen · 189 lines · 0 tokens per session scan A f477079a1334
deep-analyze is a command published in the GitHub repository dansasser/claude-code-marketplace (9 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,434 tokens. 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 2026-08-31.
deep-analyze compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| deep-analyzedansasser/claude-code-marketplace | Command | 9 | 6mo ago | MIT | A | 0 | Claude Code |
| diff-reviewcoco-research/coco | Command | 630 | today | Apache-2.0 | A | 11 | Claude Code |
| review-branchdamusix/atomic-claude | Command | 116 | yesterday | MIT | A | 35 | Claude Code |
| initazrtydxb/procoder | Command | 211 | yesterday | Apache-2.0 | A | 16 | Claude Code |
| refactorRchGrav/claudebox | Command | 1.2k | 1mo ago | MIT | A | 9 | Claude Code |
| spec-trace-requirementsrjmurillo/ai-agents | Command | 49 | today | MIT | A | 0 | GitHub Copilot |
| merge-conflict-analysisrjmurillo/ai-agents | Command | 49 | today | MIT | A | 0 | GitHub Copilot |