Low confidence โ this score is based on limited public data (mostly aggregate ratings, with little independent discussion or review detail), so it may not reflect real-world quality.
What it is
A repository analysis tool that extracts coding patterns, team conventions, and project-specific knowledge from Git history to create guidance files for AI coding assistants. ECC Tools is a non-AI developer utility that sits between your codebase and tools like Claude Code or Cursor. Software engineers use it to teach their AI assistants about internal APIs, coding standards, and architectural decisions that wouldn't be in the assistant's training data.
At a glance
The tool analyzes your repository's commit history and patterns to automatically generate custom skills and configurations for AI coding assistants like Claude Code and Cursor, rather than just providing generic prompts.
Moderate evidenceQuality score
ECC Tools GitHub App that turns repo history into reusable AI coding guidance, with private-repo analysis capped on Pro.
This score is our editorial judgment, computed automatically from the sources, weights, and dates shown above. It reflects the data we could verify as of August 23, 2026, not a guarantee or statement of fact about ECC Tools. Third-party ratings and quotes belong to their original platforms and authors. Thin data lowers our confidence label, and we say so instead of guessing. Work on ECC Tools? Dispute any datapoint and we will review it, publish your response, and correct verified errors.
Plans
10 analyses/month for public repos; Pro $19/mo for private repos
Capabilities
Provides utilities that help programmers build, test, and ship software faster
Automates multi-step processes and routes tasks across your tools and team
Questions
ECC Tools is an open-source harness system that analyzes your git repository history to create standardized workflows and security rules for AI coding assistants like Claude Code, Cursor, and OpenCode. It transforms recurring patterns from your team's development history into reusable skills, agents, and automated checks, ensuring consistent AI-assisted development across your entire team.
ECC Tools offers a free tier for public repositories with 10 analyses per month and 200 commits per run. For private repositories and team features, the Pro plan costs $19 per active developer seat monthly, with an annual option at $22,800 (about 17% savings). Enterprise plans with unlimited analyses and custom governance are also available.
ECC Tools integrates as a GitHub App that automatically analyzes your repository's git history and workflow patterns. It examines up to 200 commits per run on the free tier (1,000 on Pro) and generates pull requests with suggested skills and defaults based on your team's recurring development patterns. The system continuously learns from developer corrections to improve future suggestions.
AgentShield is ECC Tools' security scanning component that analyzes AI agent configurations, hooks, and MCP servers for vulnerabilities. It ensures that productivity gains from AI coding assistants don't compromise your security posture by scanning configurations and supporting policy packs for enterprise governance.
ECC Tools is designed to work with popular AI coding assistants including Claude Code, Codex, Cursor, and OpenCode. It creates standardized workflows and reusable skills that can be applied consistently across these different AI tools, rather than having each developer start from scratch with each platform.
ECC Tools comes with an MIT-licensed open-source foundation that includes 261 pre-built skills and 64 agents. These provide a starting point for teams, which can then be customized and expanded based on your specific repository patterns and development workflows.
Private repository analysis requires the Pro plan at $19 per active developer seat monthly. The free tier only supports public repositories, but Pro subscribers get private repo analysis, PR-triggered audits, AgentShield security scanning, and priority support.
ECC Tools generates pull requests with suggested skills and defaults that teammates can review and adopt, creating a collaborative approach to standardization. The system captures team patterns and corrections to build atomic behaviors with confidence scoring, allowing individual developers to maintain their preferences while benefiting from team-wide consistency.
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