Apply verified self-modification patches to a software corpus after cross-model jury approval.
npx skills add https://github.com/dogekiki/SP-test --skill meta-apply-dogekiki
Please help me install this Agent Skill. Skill: meta-apply Source: https://github.com/dogekiki/SP-test/tree/main/.trae/skills/meta-apply Command: npx skills add https://github.com/dogekiki/SP-test --skill meta-apply-dogekiki
This skill solves the risk of uncontrolled self-modification by acting as a secure, human-authorized gatekeeper that validates and applies patches generated by autonomous optimization agents.
Type /meta-apply all to review and land all pending patches that have passed the cross-model jury verification.
High-intent search queries and answers about installing and using this skill.
To securely apply self-modification patches, you need a gatekeeper that enforces privilege boundaries, mandates cross-model jury verification, and requires human authorization before transitioning staged candidates to permanent code changes.
Cross-model jury verification is an independent review mechanism that validates every patch before application, ensuring autonomous optimization agents cannot land uncontrolled or unauthorized mutations directly into production code.
You track provenance by automatically stamping every applied change with author, reviewer, and verdict metadata, ensuring full auditability and structural integrity for all self-modification patches.
Yes, you can review the jury's verdict and selectively land only the safe, approved patches into your production code, preventing unauthorized direct mutations to the software corpus.
Automated patch management prevents unauthorized direct mutations by enforcing a secure privilege boundary that requires mandatory cross-model jury verification and human authorization before any permanent code changes occur.
AscendGenerate migration artifacts for MindSpeed from aligned Megatron changes.
ivegamsftRun unit tests, TypeScript checks, Docker rebuilds, and smoke tests.
caw111Apply approved meta-optimize patches to the skill corpus.
czh-ee-2023Approves and applies self-modification patches to the skill corpus after jury and human review.
