Extract recurring corrections from EVOLUTION.md and generate STEERING.md rules.
npx skills add https://github.com/xg-gh-25/SwarmAI --skill steeringify
Please help me install this Agent Skill. Skill: steeringify Source: https://github.com/xg-gh-25/SwarmAI/tree/main/backend/skills/s_steeringify Command: npx skills add https://github.com/xg-gh-25/SwarmAI --skill steeringify
This workflow identifies recurring governance corrections in EVOLUTION.md and converts them into formal, reusable STEERING.md rules, enabling consistent policy evolution.
Run the steeringify workflow to convert recurring corrections into standing rules, then review and apply them to STEERING.md.
High-intent search queries and answers about installing and using this skill.
To convert governance corrections into standing rules, this workflow extracts recurring corrections from EVOLUTION.md, groups them via C-ID cross-references, and proposes formal STEERING.md rules with de-dup checks against existing files.
Extracting rule proposals from EVOLUTION.md involves a three-stage pipeline: identifying recurring corrections, grouping related corrections into connected components by C-ID cross-references, and generating concise, testable rule proposals for STEERING.md.
Checking for duplicate rules across STEERING.md and AGENT.md is handled automatically during the rule proposal stage, performing de-dup checks against existing governance files to prevent redundant entries and maintain a consistent rule set.
Yes, you can enforce a maximum number of active rules in STEERING.md through built-in safeguards that cap active rules, detect violations, and perform de-dup checks to ensure the governance rule set remains consistent and manageable.
You need to formalize EVOLUTION.md corrections into governance rules when recurring corrections reference each other via explicit C-IDs, indicating a pattern that requires conversion into standing, reusable STEERING.md rules for consistent policy evolution.
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