Feedback Learning

What to consider before installing: - The skill is coherent with its stated purpose and requires no external credentials or network access. The included scripts operate only on a local directory under $HOME and generate reports, patterns, and promoted rules. - However, there are two important safety signals: (1) SKILL.md was flagged for unicode-control characters (possible prompt-injection), and (2) promoted rules are created automatically from user signals/hints and the agents are advised to read and apply these rules at boot. With the current default (promote at 3 occurrences in 30 days), an attacker or noisy users could poison the knowledge base and change agent behavior. Actions you can take to reduce risk: - Inspect and remove any suspicious unicode/control characters from SKILL.md before installing. - Run this skill in an isolated agent or non-production environment first to observe behavior. - Require human review before promotions: modify analyze-patterns.py to write candidate promotions to a 'pending' file instead of directly adding to genes.json, and add a manual approval step. - Increase promotion thresholds (e.g., more than 3 occurrences and/or add manual vetting), and add provenance metadata (who triggered events) and stronger deduplication to detect automated flooding. - Restrict which agents/users can call log-event.sh and ensure events.jsonl is writable only by a limited user/group (set filesystem permissions on the shared directory). - Remove or clarify the LLM refinement comment: if you plan to have an LLM refine rules, make that explicit and add constraints and auditing for any LLM-run step. If you cannot perform the above checks or do not trust the source, do not install the skill into production agents. If you proceed, enforce human review of promoted rules and lock down write access to the shared learning directory.