Synthesize accumulated observations into system evolution proposals for human approval.
npx skills add https://github.com/Miosa-osa/canopy --skill rethink-miosa-osa
Please help me install this Agent Skill. Skill: rethink Source: https://github.com/Miosa-osa/canopy/tree/main/library/skills/learning/rethink Command: npx skills add https://github.com/Miosa-osa/canopy --skill rethink-miosa-osa
Synthesize accumulated observations into system evolution proposals. Fires when observation count reaches threshold. 5-phase process: triage, methodology updates, pattern detection, proposal generation, and human approval. Never auto-implements — always proposes changes for review.
Compose a rethink request for a target category (e.g., /rethink "process") to produce a proposal set for review.
High-intent search queries and answers about installing and using this skill.
To synthesize accumulated workflow observations into actionable system proposals, this Skill triages collected data, detects patterns, and generates reviewable proposals. It requires a sufficient observation count across categories to trigger design changes.
Generating system evolution proposals involves a 5-phase process: triage observations, update methodology, detect patterns, generate proposals, and secure human approval. It produces concrete proposals with rationale and impact rather than automated changes.
You cannot auto-implement system changes based on detected workflow patterns. The Skill strictly enforces human approval before any implementation, preventing autonomous alterations and ensuring all design changes are reviewed.
You need human approval for system evolution proposals whenever observation thresholds are met and design changes are justified. The workflow always routes generated proposals to a human review gate to prevent autonomous modifications to agents or workflows.
The proposal generation workflow does support configurable thresholds and history. This allows you to control when observation counts justify design changes and to track the evolution of governance loops over time.
The best way to evolve agent workflows based on observed governance signals is to accumulate observations until threshold, then run a triage and pattern detection workflow to generate concrete, reviewable proposals for human approval.
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