evolver-fixedA self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.
Install via ClawdBot CLI:
clawdbot install oliver-smith-2048/evolver-fixedGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
Report → https://github.com/EvoMap/evolver/pull/139Hardcoded 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/Generated May 10, 2026
A SaaS company uses the Evolver to automatically detect and patch production bugs by analyzing error logs and runtime history. The agent applies fixes directly to the codebase, reducing downtime and manual debugging effort.
An AI research lab deploys the Evolver to refine ML training pipelines by adjusting hyperparameters, data preprocessing steps, or model architectures based on performance metrics. The agent evolves the pipeline autonomously between training runs.
A DevOps team integrates the Evolver to monitor server load, disk usage, and process health. The agent automatically restarts failed services, cleans up disk space, or adjusts resource limits to maintain system stability.
A fintech startup uses the Evolver to automatically create GitHub releases, generate changelogs from commit history, and publish updated assets to the EvoMap network. The agent handles versioning and release notes with no human intervention.
An enterprise deploys the Evolver to continuously update a shared memory graph, adding new insights, relationships, and reflections from agent interactions. The evolved memory improves decision-making across multiple AI agents.
Offer a subscription service where the Evolver monitors and automatically repairs customer applications, reducing downtime and support costs. Revenue is generated from monthly or annual fees based on the number of agents or codebases managed.
Provide continuous optimization of ML pipelines as a managed service. Customers pay based on the complexity of the pipeline and the frequency of evolution cycles, benefiting from improved model performance without manual tuning.
License the Evolver as part of a broader DevOps automation platform that includes self-healing, monitoring, and release management. Revenue comes from one-time license fees plus annual maintenance and support contracts.
💬 Integration Tip
Start by setting A2A_NODE_ID and A2A_HUB_URL environment variables, then run `node index.js` for automated evolution. Review mode with `--review` is recommended for initial runs to inspect changes before solidification.
Scored Jun 29, 2026
Calls external URL not in known-safe list
https://evomap.aiUses known external API (expected, informational)
api.github.comAI Analysis
The skill requires broad permissions (network, shell) and sends data to external endpoints (evomap.ai, api.github.com), which is consistent with its self-evolution purpose but introduces inherent risk. The presence of a hardcoded credential pattern and potentially destructive shell commands (rm -rf /) indicates insufficient safety controls, though these may be examples or placeholders. The external data sink to an undocumented endpoint is concerning but appears related to the skill's core protocol.
Audited Apr 17, 2026 · audit v1.0
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