open-steps
Converts raw agent outputs into actionable documentation and reports, reducing handoff friction between automated systems and human stakeholders who need cle…
Skills that translate your coding agent's output into plain language: honest reports, straight verdicts, steps you can follow. MIT.
- Generate step-by-step instructions from complex code analysis reports for non-technical stakeholders
- Convert AI-generated technical findings into actionable plain-English verdicts for decision makers
- Translate debugging output into clear follow-up steps your team can execute immediately
Converts raw agent outputs into actionable documentation and reports, reducing handoff friction between automated systems and human stakeholders who need clear, auditable decision trails.
Engineering teams integrating AI coding agents who need human-readable summaries and step-by-step remediation guidance for stakeholders and compliance reviews.
https://github.com/kharmanskyi/open-steps
By kharmanskyi
How to Get It
claude plugins install kharmanskyi/open-steps
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate step-by-step instructions from complex code analysis reports for non-technical stakeholders
Trust Signals Auto-scanned
Community Pulse Emerging
Discussed on Hacker News
- Steve Jobs Presents – OpenStep's Interface Builder — Hacker News · 2 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 128 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 128 GitHub stars; contributors unknown; last commit 0d ago; license MIT.