- run_training.py / run_command.py: subprocess.TimeoutExpired carries
captured output as bytes on POSIX even with text=True; decode it
before log combining so timed-out runs no longer crash on Linux.
- write_explore_bundle.py: guard selected_idea / patch_surface_summary
against explicit None so blocked manifests (no idea passes the gate)
render COMPARABILITY_REPORT.md instead of raising AttributeError.
Fixes test_training_lane_routing.py, test_research_explore_blocked_manifest.py,
and test_research_explore_campaign_abandon.py on Linux.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HT2VAaQodjqTJdjBHSStxA
- Introduced language policy to ensure human-readable outputs while maintaining machine-readable stability.
- Created output specification detailing required output files and their formats.
- Established patch policy to guide conservative modifications to repository code.
- Defined research safety principles to prioritize observable and reviewable research progress.
- Implemented orchestration script for minimal README-first reproduction, including command extraction and execution handling.
- Added functions for managing assets, estimating training duration, and building context for reproducibility.
- Implemented `lookup_sources.py` to facilitate a free-first, cache-first research lookup pass, including functions for deduplication, seed record collection, and provider record resolution.
- Introduced `source_mapping.py` for source module lookup and interface diffing, featuring functions to select source records, build target location maps, and generate minimal patch plans.
- Enhanced data normalization and evidence class handling to improve the accuracy of source mapping.
- Added utility functions for writing module candidates and interface diffs to markdown files for better documentation.
- Introduced `test_research_explore_campaign_abandon.py` to validate abandonment of far-from-SOTA baselines.
- Added `test_research_explore_campaign_checkpoint.py` to ensure human checkpoint gating for near-tied ideas.
- Created `test_research_explore_campaign_flow.py` to verify the overall campaign flow and execution policies.
- Documented the `research_campaign_spec.md` outlining the structure and requirements for campaign JSON/YAML configurations.
- Added `run_training.py` modifications to improve command execution handling.
- Introduced `explore-module-roadmap.md` to outline the evolution of the explore lane.
- Created `explore-variant-spec.md` for defining variant specifications in exploratory runs.
- Implemented regression tests for non-training and training variant execution in `test_research_explore_nontraining_execution.py` and `test_research_explore_variant_execution.py`.
- Developed `plan_code_changes.py` to generate exploratory code-change plans.
- Added `run_command.py` for executing short non-training commands and normalizing evidence.
- Added `research-explore` skill to facilitate end-to-end exploratory work on top of `current_research`.
- Updated `explore-code` and `explore-run` skills to clarify boundaries and usage.
- Enhanced documentation for all skills to reflect new orchestrator capabilities and requirements.
- Implemented orchestration logic in `scripts/orchestrate_explore.py` to manage exploratory code and run changes together.
- Created output structure for exploratory results in `explore_outputs/`.
- Added regression tests for the new orchestrator to ensure proper functionality and integration.
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