Advanced AI Assess Findings: Automate Report Writing

Advanced AI Assess Findings: Automate Report Writing

The Advanced AI Assess Findings skill automates the report writing process by compiling analysis data into a structured report. It processes the deterministic run-context.json and the layer scorecard, including verbatim cross-layer findings, lying signals, and suggested Top 3 Actions. This skill is triggered automatically when the /assess orchestrator reaches the report-writing stage, enhancing reproducibility and accuracy in the report assembly.

What this skill does

• Upon initiation by the /assess orchestrator, the skill accesses the deterministic core data from $REPO_ROOT/.assess/run-context.json.
• It incorporates the scorecard provided by the assess-layer-scorer, which includes a 0-8 score, per-layer verdicts, and maturity labels.
• The skill assembles the required components into a cohesive report: the scorecard, snapshots of results, verbatim cross-layer findings, lying signals, and the Top 3 Actions.
• The report-writing process maintains a clear division between deterministic data insertion and generated prose, ensuring consistency regardless of AI model use.

Who it is for

• Developers and technical teams utilizing AI coding assistants like Claude Code, Cursor, and Codex who require streamlined reporting of their assessments.
• Project managers seeking reliable and reproducible reports for their evaluation processes.

Use cases

• AI development teams automating their report creation tasks following an assessment of coding projects, leading to consistent documentation outputs.
• Technical leads reviewing comprehensive assessment reports to inform decision-making and future action plans.

Technical details

• Compatible with AI coding assistants such as Claude Code, Cursor, and Codex.
• Operates by integrating inputs from run-context.json and coordination with the assess-layer-scorer to generate a detailed report.
• Relies on the deterministic/LLM synergy for enhanced report reproducibility.

For authorised security testing, defensive research and educational use only.

Source & Licence

This package is built on open-source work published by bjcoombs (bjcoombs/ai-native-toolkit) and distributed under Apache-2.0. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted under the Apache License 2.0, which also includes an express patent grant. Attribution and any NOTICE file must be retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.