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Fix #63: mark unimplemented features as planned in README #98

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Fix #63: mark unimplemented features as planned in README #98

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13 changes: 11 additions & 2 deletions README.md
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Expand Up @@ -9,8 +9,8 @@ Abathur coordinates multiple AI agents to work on complex tasks. It handles task
- **Task orchestration**: Break down work into a DAG of subtasks, route them to specialized agents, run them in parallel waves
- **Git worktree isolation**: Each task runs in its own worktree so agents can work on different parts of the codebase simultaneously without stepping on each other
- **Three-tier memory**: Working, episodic, and semantic memory with configurable decay. Agents can query past context and learnings
- **Agent evolution**: Track success rates per agent template version. Underperforming agents get refined, regressions get reverted
- **Meta-planning**: A meta-planner agent analyzes incoming tasks, detects capability gaps, and can spawn new specialist agents when needed
- **Agent evolution** *(planned)*: Track success rates per agent template version. Underperforming agents get refined, regressions get reverted
- **Meta-planning** *(planned)*: A meta-planner agent analyzes incoming tasks, detects capability gaps, and can spawn new specialist agents when needed

## Prerequisites

Expand Down Expand Up @@ -205,6 +205,15 @@ status_done = "COMPLETED"

Requires `CLICKUP_API_KEY` in the environment.

## Roadmap

The following features are designed but not yet implemented:

- **Agent evolution** — Success rate tracking per agent template version, automatic template refinement, and regression detection/rollback
- **Meta-planning** — Capability gap detection, dynamic specialist agent spawning, and task routing optimization

Contributions toward these features are welcome! See the issues labeled with these topics for discussion.

## Contributing

See [CONTRIBUTING.md](CONTRIBUTING.md) for development setup, coding conventions, and the PR process.
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