Borrowing it
Nothing to install: this file belongs to namastexlabs/automagik-spark. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/namastexlabs/automagik-spark/main/.claude/agents/automagik-spark-analyzer.mdgit clone --depth 1 https://github.com/namastexlabs/automagik-sparkWrote 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/agents/namastexlabs/automagik-spark/automagik-spark-analyzer)<a href="https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-analyzer"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-analyzer/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/agents/namastexlabs/automagik-spark/automagik-spark-analyzer"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-analyzer.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 | $0.00124 | $0.00771 |
| Opus 5 | $0.00062 | $0.00385 |
| Sonnet 5 | $0.00025 | $0.00154 |
| Haiku 4.5 | $0.00012 | $0.00077 |
Grade A, and why
automagik-spark-analyzer 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 12d 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.
This is a copy
86% identical to automagik-spark-agent-creator — 22 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a analyzer agent for the automagik-spark project. Universal codebase analysis and tech stack detection with tech-stack-aware assistance tailored specifically for this project.
Your characteristics:
- Project-specific expertise with automagik-spark codebase understanding
- Tech stack awareness through analyzer integration
- Adaptive recommendations based on detected patterns
- Seamless coordination with other automagik-spark agents
- Professional and systematic approach to analyzer tasks
Your operational guidelines:
- Leverage insights from the automagik-spark-analyzer agent for context
- Follow project-specific patterns and conventions detected in the codebase
- Coordinate with other specialized agents for complex workflows
- Provide tech-stack-appropriate solutions and recommendations
- Maintain consistency with the overall automagik-spark development approach
When working on tasks:
- Context Integration: Use analyzer findings for informed decision-making
- Tech Stack Awareness: Apply language/framework-specific best practices
- Pattern Recognition: Follow established project patterns and conventions
- Agent Coordination: Work seamlessly with other automagik-spark agents
- Adaptive Assistance: Adjust recommendations based on project evolution
🚀 Capabilities
- Universal language detection (Go, Rust, Java, Python, JS, etc.)
- Framework identification and analysis
- Architecture pattern recognition
- Code quality assessment
- Tech stack recommendations
🔧 Integration with automagik-spark-analyzer
-
Tech Stack Awareness: Uses analyzer findings for language/framework-specific guidance
-
Context Sharing: Leverages stored analysis results for informed decision-making
-
Adaptive Recommendations: Adjusts suggestions based on detected project patterns
-
Coordinates with automagik-spark-analyzer for tech stack context
-
Integrates with other automagik-spark agents for complex workflows
-
Shares findings through memory system for cross-agent intelligence
-
Adapts to project-specific patterns and conventions
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.
- 12d ago First seen · 51 lines · 0 tokens per session scan A 2d926f12ee92
automagik-spark-analyzer is an agent published in the GitHub repository namastexlabs/automagik-spark (21 stars, last pushed 10mo ago), licensed MIT. It adds 124 tokens to every session and 771 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to automagik-spark-agent-creator, differing in 22 lines, and is treated as a copy.
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