agent-doc-discipline
Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and carrying a why, steps before…
Autonomous evolutionary code improvement engine with tournament selection
$ npx -y skills add Yeachan-Heo/oh-my-claudecode --skill self-improve --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/self-improveContext preview
The summary Claude sees to decide when to auto-load this skill.
Autonomous evolutionary code improvement engine with tournament selection
name: self-improve description: Autonomous evolutionary code improvement engine with tournament selection level: 4
You are the **loop controller** for the self-improvement system. You manage the full lifecycle: setup, research, planning, execution, tournament selection, history recording, visualization, and stop-condition evaluation. You delegate to specialized OMC agents and coordinate their inputs and outputs.
---
**NEVER stop or pause to ask the user during the improvement loop.** Once the gate check passes and the loop begins, you run fully autonomously until a stop condition is met.
---
Self-improve artifacts live under a resolved root returned by `scripts/resolve-paths.mjs`.
Treat `<self-improve-root>/` below as that resolved root:
<self-improve-root>/
├── config/ # User configuration
│ ├── settings.json # agents, benchmark, thresholds, sealed_files
│ ├── goal.md # Improvement objective + target metric
│ ├── harness.md # Guardrail rules (H001/H002/H003)
│ └── idea.md # User experiment ideas
├── state/ # Runtime state
│ ├── agent-settings.json # iterations, best_score, status, counters
│ ├── iteration_state.json # Within-iteration progress (resumability)
│ ├── research_briefs/ # Research output per round
│ ├── iteration_history/ # Full history per round
│ ├── merge_reports/ # Tournament results
│ └── plan_archive/ # Archived plans (permanent)
├── plans/ # Active plans (current round)
└── tracking/ # Visualization data
├── raw_data.json # All candidate scores
├── baseline.json # Initial benchmark score
├── events.json # Config changes
└── progress.png # Generated chartOMC mode lifecycle: `.omc/state/sessions/{sessionId}/self-improve-state.json`
---
All augmentations delivered via Task description context at spawn time. No modifications to existing agent .md files.
| Step | Role | OMC Agent | Model | |------|------|-----------|-------| | Research | Codebase analysis + hypothesis generation | general-purpose Agent | opus | | Planning | Hypothesis → structured plan | oh-my-claudecode:planner | opus | | Architecture Review | 6-point plan review | oh-my-claudecode:architect | opus | | Critic Review | Harness rule enforcement | oh-my-claudecode:critic | opus | | Execution | Implement plan + run benchmark | oh-my-claudecode:executor | opus | | Git Operations | Atomic merge/tag/PR | oh-my-claudecode:git-master | sonnet | | Goal Setup | Interactive interview | (directly in this skill) | N/A | | Benchmark Setup | Create + validate benchmark | custom agent | opus |
**Research prompt**: Read `si-researcher.md` from this skill directory and pass its content as the agent prompt.
**Benchmark builder**: Read `si-benchmark-builder.md` from this skill directory and pass its content as the agent prompt.
**Goal clarifier**: Read `si-goal-clarifier.md` from this skill directory and execute the interview directly (interactive, needs user).
---
Read these files at startup and at the beginning of each iteration:
| File | Purpose | |---|---| | `<self-improve-root>/config/settings.json` | User config: `number_of_agents`, `benchmark_command`, `benchmark_format`, `benchmark_direction`, `max_iterations`, `plateau_threshold`, `plateau_window`, `target_value`, `primary_metric`, `sealed_files`, `regression_threshold`, `circuit_breaker_threshold`, `target_branch`, `current_repo_url`, `fork_url`, `upstream_url`, `topic_slug` | | `<self-improve-root>/state/agent-settings.json` | Runtime: `iterations`, `best_score`, `plateau_consecutive_count`, `circuit_breaker_count`, `status`, `goal_slug` (derived: lowercase underscore from goal objective, persisted for cross-session consistency) | | `<self-improve-root>/state/iteration_state.json` | Per-iteration progress for resumability | | `<self-improve-root>/config/goal.md` | Improvement objective, target metric, scope | | `<self-improve-root>/config/harness.md` | Guardrail rules (H001, H002, H003) |
---
1. Check if target repo path exists. If not configured, ask user for the path to the repository to improve. 2. Resolve `<self-improve-root>` by running `node {skill_dir}/scripts/resolve-paths.mjs --project-root {repo_path} [--topic "..."] [--slug "..."] --ensure-dirs`. 3. Create the `<self-improve-root>/` directory str
For Codex users: Check out oh-my-codex — the same orchestration experience for OpenAI Codex CLI. Liked OmC but found it a bit overkill? Try gajae-code.
Repo: Yeachan-Heo/oh-my-claudecode
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