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Overview
Practice cases
Features
Workflows
Projects and chatsLocal workspaceLong-term memoryScheduled tasksLong-running workNotificationsSitesVisualizationsPets
Capabilities
File handlingImage inputAttach an appWeb searchBrowserUse everyday ChromeVoiceImage generationPluginsSelf-evolution
Reusable experience
GenesCapsulesEvolver skillsEvolution events.gepx evolution archives
Swarm
Using swarmContinuous swarmRecursive tasksRecovery and follow-upDevice collaboration
Reference
CommandsSlash commandsSettingsTroubleshooting
Configuration
Developers
Security
Administration
EvoX ドキュメント/Product/Optimize

Self-evolution

Find problems in task outcomes, verify improvements, and retain experience for future work.

Evolver is the engine that runs evolution workflows, either independently or through an application integration. It is distinct from ordinary chats, scheduled tasks, and long-term goals. Execution and allowed changes depend on the configured environment.

When to use it

Self-evolution needs a reproducible problem, a clear improvement target, and a way to verify results. Define the task before choosing a direction.

DirectionSuitable situationHow to judge the result
RepairErrors, failed tests, or broken behaviorThe original issue is resolved and related behavior still works
OptimizePerformance, cost, latency, or code quality needs improvementCompare before and after, checking for regressions
InnovateA required capability or integration is missingNew behavior meets explicit acceptance criteria
ExploreRepeated attempts produce no useful improvementFind a testable problem or approach, not simply more changes

These are evolution intents, not four mandatory sequential steps.

How a cycle works

  1. Gather signals: Review errors, test results, task records, or other available evidence.
  2. Choose a direction: Decide whether to repair, optimize, innovate, or explore.
  3. Form a plan: Define scope, validation, and stop conditions.
  4. Execute and verify: Work within the allowed scope and run the appropriate checks.
  5. Record the outcome: Retain validation results, environment details, and useful logs.

Finishing a change does not mean validation passed. When an attempt yields no improvement, record why rather than treating unverified work as a successful lesson.

Prepare before starting

  • Goal: Describe a concrete problem or desired change, not just “keep improving.”
  • Context: Provide the workspace, errors, and previous attempts to avoid repeating investigations.
  • Boundaries: Define allowed changes and actions that require separate approval.
  • Validation: Identify tests, comparison metrics, or manual acceptance checks.
  • Stop conditions: Specify when to finish, pause, or hand work to a person.

For a recurring error, preserve the reproduction conditions and failing result. After a fix, verify under the same conditions and check related behavior.

Retain and reuse experience

Useful experience explains which approach worked under which conditions. Include the problem, key steps, validation results, and limitations.

Evolver uses assets such as Genes, Capsules, and EvolutionEvents to record methods, outcomes, and the evolution process. Check the environment and applicability before reuse; success on an earlier task does not remove the need to validate a new one.

  • Genes: Reusable methods.
  • Capsules: Outcomes and experience assets.
  • Evolution events: Process records.

Loops and exploration

Strategies prioritize the kind of work, loop settings determine whether execution continues, and change boundaries limit each cycle.

Exploration can broaden the search after saturation or repeated no-op cycles, for example by checking TODOs, stale files, or reusable assets. It still needs cooldowns and stop conditions rather than indefinite execution or aimless changes.

Confirm the workspace and validation approach in a single cycle or review mode before enabling continuous execution. See Evolution behavior for parameters; standalone Evolver settings are not desktop task switches.

Permissions and approval

Strategies and loops do not expand permissions. External access, deletion, commits, asset publication, and production writes retain their own authorization and approval requirements.

When validation fails, do not continue to publication or record a reusable success. Follow the environment's rollback configuration when recovery is needed, preserving unrelated workspace changes.

Troubleshooting

  • Repeated cycles without useful improvement: Review signals, goals, and stop conditions instead of simply running longer.
  • Changes with no clear evidence of success: Establish reproduction and acceptance checks before judging the result.
  • Old experience fails in a new environment: Check dependencies, versions, and scope, then validate again.
  • No matching desktop switch: This page describes the evolution process. Consult developer and configuration guides for standalone engine installation and settings.

Related docs

  • Evolution behavior
  • Install Evolver CLI
  • Evolver repository
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