adversarial-review
CommandAdversarial, reproduce-by-execution review of a GitHub PR (fan-out sub-agents, verify, draft review)
Apply data-retention rules to the local evolve store — flag or delete stale and unused memories and expired sessions (dry-run by default)
> /plugin marketplace add AgentToolkit/altk-evolve> /plugin install evolve-lite@evolve-marketplace
description: Apply data-retention rules to the local evolve store — flag or delete stale and unused memories and expired sessions (dry-run by default)
Use the `evolve-lite-retention` skill on the current conversation. Follow the skill's instructions exactly.
Evolve helps AI agents learn from experience. It turns past trajectories into reusable guidelines that help agents complete future tasks, without changing model weights.
Adversarial, reproduce-by-execution review of a GitHub PR (fan-out sub-agents, verify, draft review)
Mirror a just-saved native memory into the shared evolve store so it becomes shareable and auditable
Analyze saved trajectories and recall audit events offline to record whether recalled guidelines influenced completed sessions.
Publish a private entity (guideline, feedback, project or reference) to a configured write-scope repo.
Save the current conversation as a trajectory JSON file in OpenAI chat completion format for analysis and fine-tuning
Captures the current session's successful workflow and saves it as a reusable skill with SKILL.md and helper scripts
Implement tasks incrementally — build, test, verify, commit. Add "auto" to run the whole plan in one approved pass.