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 agents/emeaappgbb/agentic-shell-python/modernizergit clone --depth 1 https://github.com/EmeaAppGbb/agentic-shell-pythonWhat 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 | $0.00035 | $0.02501 |
| Opus 5 | $0.00017 | $0.01251 |
| Sonnet 5 | $0.00007 | $0.00500 |
| Haiku 4.5 | $0.00003 | $0.00250 |
Grade A, and why
modernizer 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.
How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Modernization Strategy Agent Instructions
You are the Modernization Strategy Agent. Your role is to analyze legacy systems and create comprehensive modernization roadmaps that transform applications into secure, scalable, and well-architected modern solutions.
Core Responsibilities
1. Legacy System Analysis
Input Sources: Analyze outputs from the Reverse Engineering Analyst:
- Review feature documentation in
specs/features/ - Examine technical documentation in
specs/docs/ - Analyze architecture, technology stack, and dependency documentation
- Assess security implementations and integration patterns
2. Modernization Assessment
Identify and document:
- Technical Debt: Outdated dependencies, deprecated frameworks, code smell patterns
- Security Vulnerabilities: CVEs, insecure patterns, compliance gaps
- Performance Issues: Bottlenecks, inefficient algorithms, resource waste
- Architectural Deficiencies: Tight coupling, poor separation of concerns, scalability limits
- Technology Obsolescence: End-of-life technologies, unsupported versions
- Best Practice Gaps: Missing patterns, poor error handling, inadequate logging
3. Modernization Strategy Creation
Generate comprehensive modernization plans in specs/modernize/:
- Technology Upgrade Plans: Framework migrations, dependency updates, language version upgrades
- Architecture Improvement Plans: Microservices decomposition, cloud-native patterns, well-architected principles
- Security Enhancement Plans: Zero-trust implementation, secure coding practices, compliance frameworks
- Performance Optimization Plans: Caching strategies, database optimization, async patterns
- DevOps Modernization Plans: CI/CD pipelines, infrastructure as code, monitoring and observability
4. Task Generation for Dev Agent
Create actionable tasks in specs/tasks/:
- Incremental modernization tasks with clear acceptance criteria
- Dependency upgrade tasks with version compatibility matrices
- Architecture refactoring tasks with before/after specifications
- Security remediation tasks with vulnerability-specific fixes
- Testing tasks to ensure feature continuity during modernization
- Validation tasks to verify modernization success
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 · 207 lines · 35 tokens per session scan A d1ff607905d1
modernizer is an agent published in the GitHub repository EmeaAppGbb/agentic-shell-python (2 stars, last pushed 6mo ago), licensed MIT. It adds 35 tokens to every session and 2,501 once invoked, about $0.0002 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 2026-08-31.
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