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/dansasser/claude-code-marketplace/analyzegit 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/analyze)<a href="https://agentmods.dev/commands/dansasser/claude-code-marketplace/analyze"><img src="https://agentmods.dev/badge/commands/dansasser/claude-code-marketplace/analyze.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00767 |
| Opus 5 | $0.00000 | $0.00383 |
| Sonnet 5 | $0.00000 | $0.00153 |
| Haiku 4.5 | $0.00000 | $0.00077 |
Grade A, and why
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 4d 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.
What it actually says
Analyze File or Directory with Ollama
Analyze the specified file or directory using the ollama agent pipeline.
Usage: /analyze <file_or_directory> [focus_area]
Examples:
/analyze src/auth.py security- Security analysis of single file/analyze README.md- General analysis/analyze src/ architecture- Architecture analysis of directory/analyze src/ security- Security audit of entire directory
You are an intelligent task router for ollama-based analysis.
Task: Analyze the target at path: $1 Focus Area: $2
Your Process:
-
Check Target:
- Determine if target is file or directory
- For files: Get size and estimate tokens
- For directories: Use directory operations for efficiency
-
Select Strategy:
For Files:
- Small files (< 20KB): Direct ollama-prompt
- Large files (> 20KB): Use ollama-chunked-analyzer approach
For Directories:
- Architecture focus: Use
@./dir/:treefor structure analysis - Security focus: Use
@./dir/:search:PATTERNfor vulnerability patterns - Quality focus: Use
@./dir/:search:TODO+@./dir/:tree - General: Use
@./dir/:treethen targeted analysis
-
Directory Operations by Focus Area:
Focus Area Primary Operation Example security @./dir/:search:@./src/:search:eval,@./src/:search:passwordarchitecture @./dir/:tree@./src/:treeperformance @./dir/:search:@./src/:search:for.*in,@./src/:search:queryquality @./dir/:search:+:tree@./src/:search:TODO,@./src/:treegeneral @./dir/:tree@./src/:tree -
Invoke Agent: Use the Task tool to invoke the ollama-task-router agent:
- Pass the target path: $1
- Pass the focus area: $2
- Agent uses appropriate directory operations
- Agent handles model selection and execution
-
Agent Will:
- Detect if target is file or directory
- Select appropriate model (kimi-k2-thinking, deepseek, qwen3-vl)
- Use directory operations for directories
- Route to chunked analyzer if needed
- Execute analysis with ollama-prompt
- Return synthesized results
-
Your Role:
- Receive agent's analysis report
- Present findings to user concisely
- Highlight critical issues
- Provide actionable recommendations
Focus Areas:
- security: Vulnerabilities, attack vectors, security best practices
- architecture: Design patterns, scalability, maintainability
- performance: Bottlenecks, optimization opportunities
- quality: Code quality, best practices, refactoring needs
- general: Comprehensive overview
Directory Analysis Benefits:
@./dir/:treeuses ~500 tokens vs ~15,000 for reading files individually@./dir/:search:PATTERNfinds specific issues across entire codebase- More efficient and comprehensive than file-by-file analysis
Remember: This delegates to ollama to save your context budget!
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.
- 4d ago First seen · 83 lines · 0 tokens per session scan A fd0238a6176c
analyze is a command published in the GitHub repository dansasser/claude-code-marketplace (9 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 767 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.
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
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Create or update the feature specification from a natural language feature description.
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Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.