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description: Selects required BitLesson entries for a specific sub-task. Use before execution for every task or sub-task.
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model: haiku
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tools: Read, Grep
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---
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# BitLesson Selector
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You select which lessons from `bitlesson.md` must be applied for a given sub-task.
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## Input
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You will receive:
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- Current sub-task description
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- Related file paths
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- The project `bitlesson.md` content
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## Cross-Agent Review Context
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- This agent markdown serves as the prompt specification for BitLesson selection.
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- Runtime execution happens via `scripts/bitlesson-select.sh`, which routes to Codex CLI (`codex exec`) for `gpt-*` models or Claude CLI (`claude --print`) for Claude models (`haiku`, `sonnet`, `opus`), based on the configured `bitlesson_model`.
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- Your lesson selection will be consumed by Claude and can be reviewed by Codex in later rounds.
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- Return deterministic output so cross-agent review can validate your decision quickly.
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## Decision Rules
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1. Match only lessons that are directly relevant to the sub-task scope and failure mode.
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2. Prefer precision over recall: do not include weakly related lessons.
Copy file name to clipboardExpand all lines: commands/start-rlcr-loop.md
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@@ -68,8 +68,8 @@ If the pre-check passed (or was skipped), execute the setup script to initialize
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This command starts an iterative development loop where:
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1. You execute the implementation plan with task-tag routing
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-`coding` tasks: Claude executes directly
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-`analyze` tasks: execute via `/humanize:ask-codex`
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-`coding` tasks: execute via the configured coding worker (see `coding_worker_model` config key)
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-`analyze` tasks: execute via the configured analyzing worker (see `analyzing_worker_model` config key)
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2. Write a summary of your work to the specified summary file
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3. When you try to exit, Codex reviews your summary
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4. If Codex finds issues, you receive feedback and continue
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### Key Features
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1.**Acceptance Criteria**: Each task maps to a specific AC - nothing can be "forgotten"
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2.**Task Tag Routing**: Every task should carry `coding` or `analyze` tag from plan generation
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-`coding -> Claude`, `analyze -> Codex`
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-`coding -> worker`, `analyze -> analyzer`
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3.**Plan Evolution Log**: If you discover the plan needs changes, document the change with justification
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4.**Explicit Deferrals**: Deferred tasks require strong justification and impact analysis
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5.**Full Alignment Checks**: At configurable intervals (default every 5 rounds: rounds 4, 9, 14, etc.), Codex conducts a comprehensive goal alignment audit. Use `--full-review-round N` to customize (min: 2)
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3.**Be thorough**: Include details about what was implemented, files changed, and tests added
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4.**No cheating**: Do not try to exit the loop by editing state files or running cancel commands
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5.**Trust the process**: Codex's feedback helps improve the implementation
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6.**Delegated agent context is mandatory**: Every delegated agent call must explicitly mention the worker/reviewer relationship and that review is **independent** (cross-vendor style), even if all models are OpenAI today.
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## BitLesson Workflow (Project Level)
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Each project must maintain its own `.humanize/bitlesson.md` file.
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If missing, `start-rlcr-loop` initializes it automatically with a strict template.
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Per round requirements:
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1. Read `.humanize/bitlesson.md` before execution
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2. Run `bitlesson-selector` for each task/sub-task
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3. Apply selected lesson IDs (or `NONE`) during implementation
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4. Include `## BitLesson Delta` in the round summary with `Action: none|add|update`
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If a problem is solved only after multiple rounds, add or update a precise lesson entry in `.humanize/bitlesson.md` (specific problem + specific solution).
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By default, empty `.humanize/bitlesson.md` does not block `Action: none`; use `--require-bitlesson-entry-for-none` to enforce strict blocking.
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## Stopping the Loop
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The RLCR loop has two phases within the active loop:
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1.**Implementation Phase**: Work by task tags (`coding -> Claude`, `analyze -> /humanize:ask-codex`), then Codex reviews your summary
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1.**Implementation Phase**: Work by task tags (`coding -> configured coding worker via coding_worker_model`, `analyze -> configured analyzing worker via analyzing_worker_model`), then Codex reviews your summary
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2.**Review Phase**: After COMPLETE, `codex review` checks code quality with `[P0-9]` severity markers
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The `--base-branch` option specifies the base branch for code review comparison. If not provided, it auto-detects from: remote default > local main > local master.
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