repo2A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.
Install via ClawdBot CLI:
clawdbot install mmmoeny/repo2Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Hardcoded API key or token pattern found in skill definition
ghp_xxxxxxxx...Potentially destructive shell commands in tool definitions
rm -rf /Accesses system directories or attempts privilege escalation
/proc/Calls external URL not in known-safe list
https://github.com/autogame-17/evolver/releases`Generated Mar 21, 2026
Integrate the Capability Evolver into a CI/CD pipeline for a software development team. It analyzes runtime logs from automated tests and deployments to autonomously suggest code patches for recurring errors, reducing manual debugging time. This is ideal for agile environments where rapid iteration is key.
Deploy the skill within an AI-powered customer service chatbot to monitor conversation histories and failure patterns. It can automatically refine the chatbot's response generation logic or memory prompts to improve accuracy and user satisfaction over time, ensuring continuous learning without human intervention.
Use the evolver in a research lab to process large datasets from experiments. By analyzing runtime errors in data processing scripts, it can propose optimizations or fixes to analysis algorithms, accelerating scientific discovery and reducing manual code maintenance for researchers.
Implement the skill on an e-commerce website to monitor backend service logs and transaction failures. It identifies inefficiencies or bugs in payment or inventory systems and applies protocol-constrained patches to improve uptime and reliability, minimizing revenue loss from downtime.
Offer the Capability Evolver as a cloud-based service where customers pay a monthly fee for access to automated self-improvement features. Revenue is generated through tiered pricing based on usage levels, such as number of evolutions or data volume processed, targeting businesses seeking operational efficiency.
Sell perpetual licenses to large organizations for on-premises deployment, with optional support and customization contracts. This model provides high upfront revenue and long-term service income, appealing to industries with strict data security or compliance requirements like finance or healthcare.
Provide professional services to integrate the evolver into clients' existing AI systems or workflows, including training and ongoing optimization. Revenue comes from project-based fees and retainer agreements, ideal for companies needing tailored solutions without in-house expertise.
💬 Integration Tip
Start with the --review flag in a test environment to validate changes before full deployment, and ensure git version control is active to track evolutions and enable rollbacks if needed.
Scored Jun 17, 2026
Uses known external API (expected, informational)
api.github.comAI Analysis
The skill contains a hardcoded GitHub personal access token pattern (ghp_xxxx) which is a credential leak risk, and includes unsafe shell commands (rm -rf /) that could be destructive if executed. While the external API usage (api.github.com) is consistent with its self-evolution purpose, the presence of these high-risk patterns warrants a security warning.
Audited Apr 17, 2026 · audit v1.0
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