diffinery: Open-source, agent-first GitHub and GitHub Actions alternative that runs on your own Cloudflare account

by codician-team · MCP Server · ★ 82

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 58/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-codingai-agentsci-cdcloudflarecloudflare-containerscloudflare-workerscode-reviewcontinuous-integrationdevopsdurable-objects

Quick Facts

Stars82
Forks3
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score58/100
Open Issues1
Last Updated2026-11-06
Created2026-10-25
Platformsmcp, node
Est. Tokens~23k

About diffinery

Diffinery The open-source GitHub and GitHub Actions alternative that runs entirely on Cloudflare. Git hosting, pull requests, code review and drop-in GitHub Actions CI, with agent tasks, agent code review and plugins for Claude Code and Codex, built for teams of people and AI agents. Deploy it to your own Cloudflare account: no servers, no runner machines, nothing to patch.

Compatible Skills

These tools work well together with diffinery for enhanced workflows:

  • codra — semantic(0.42)+complementary+shared_fw(cloudflare)+same_lang+similar_pop+shared_platform (73%)
  • open-managed-agents — semantic(0.24)+complementary+shared_fw(cloudflare)+rare_topics+same_lang+similar_pop+shared_platform (71%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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