#+TITLE: Multi-Lens Code Review Workflow Testing on Orch #+DATE: 2025-12-26 #+KEYWORDS: code-review, lenses, orch, beads, molecules, LLM-in-the-loop, parallel-agents #+COMMITS: 3 #+COMPRESSION_STATUS: uncompressed * Session Summary ** Date: 2025-12-26 (Continuation of 2025-12-24 session) ** Focus Area: Testing multi-lens code review workflow on orch codebase * Accomplishments - [X] Recovered session context from compaction (continued from 2025-12-24 ADR/lenses session) - [X] Ran 3 code review lenses (smells, dead-code, redundancy) on orch/src/orch/ via parallel Task agents - [X] Synthesized findings across all lenses using LLM judgment - [X] Filed 4 actionable beads issues in orch repo based on synthesis - [X] Validated the LLM-in-the-loop pattern for code review issue filing - [X] Synced beads in both skills and orch repos - [ ] Push to remote blocked (git server 192.168.1.108:3000 unavailable) * Key Decisions ** Decision 1: Use parallel Task agents for lens execution - Context: Need to run multiple lenses efficiently without sequential bottleneck - Options considered: 1. Sequential lens execution - simpler but slower 2. Parallel Task agents - faster, demonstrates multi-agent pattern 3. Single agent running all lenses - loses multi-model perspective - Rationale: Parallel agents match the "50-100 agents at once" vision from Yegge's patterns - Impact: 3x faster execution, demonstrates scalable pattern for larger codebases ** Decision 2: Synthesize findings before filing issues - Context: Raw lens output produces many overlapping findings - Options considered: 1. Mechanical parsing - file every finding as separate issue 2. LLM synthesis - agent applies judgment, groups related, sets priorities - Rationale: LLM-in-the-loop pattern per Yegge - agent stays involved at every step - Impact: Reduced 20+ raw findings to 4 actionable, prioritized issues ** Decision 3: File issues in target repo, not skills repo - Context: Lenses run from skills repo, findings belong to target codebase - Rationale: Issues should live where the work will be done - Impact: orch repo now has actionable refactoring tasks with proper context * Problems & Solutions | Problem | Solution | Learning | |---------|----------|----------| | bd sync in orch failed with prefix mismatch | molecules.jsonl contains skills- prefixed proto tasks | bd-k2wg filed: mol catalog needs hierarchical loading | | qwen returns empty content on some prompts | Use gpt/gemini as alternatives, filed orch-loq bug | Content filter issue or API quirk with certain prompt structures | | Remote git server unavailable | Local commits preserved, push pending | Distributed git works - local work continues despite server outage | | Context compaction lost previous session details | Summary preserved key decisions and file locations | Comprehensive summaries enable seamless session continuity | * Technical Details ** Code Changes - Total files modified: 16 (across session including prior context) - Key commits this session: - 1e64515 bd sync: 2025-12-26 01:57:15 - 9624873 update: code-review proto with LLM-in-the-loop pattern - fb15000 refactor: restructure for cross-repo deployment ** Issues Filed in Orch Four synthesized issues based on multi-lens analysis: 1. ~orch-buy~ [P2] refactor: create ModelSpec dataclass for provider parsing - Addresses primitive obsession (smells) and duplication (redundancy) - Same model:stance parsing done in 3+ places in cli.py 2. ~orch-bp3~ [P2] refactor: extract AttachmentProcessor from llm_adapter.py - Addresses bloat (500+ line file) and complexity (deep nesting) - llm_adapter.py at 590 lines, violates SRP 3. ~orch-esa~ [P2] refactor: split cli.py into command handlers - Addresses bloat (600+ lines) and smells (flag arguments) - CLI file handling multiple concerns 4. ~orch-loq~ [P2] bug: qwen returns empty content on some prompts - Discovered during lens testing - Possibly content filter or API issue ** Lens Output Highlights *** Smells Lens Findings - Deep nesting in stdin argument parsing (cli.py:314-327) - Primitive obsession with model:stance string parsing - Feature envy in llm_adapter.py (get_model_capabilities unused param) - Flag arguments changing behavior (format string in show_session) - Overloaded "status" variable name *** Dead-Code Lens Findings - Duplicate imports in llm_adapter.py (lines 10-12 vs 127-130) - Empty TYPE_CHECKING block with only pass - Unused config parameter in get_model_capabilities() - Re-exports for "backward compatibility" with no external consumers - Suspicious logic in use_llm_backend() comment vs implementation *** Redundancy Lens Findings - Temperature validation duplicated in config.py and validation.py - Alias resolution chain: cli.py -> llm_adapter.py -> models_registry.py - Error printing pattern repeated in cli.py (2x) - Cancellation handling duplicated in chat() and consensus() - Magic number 300.0 timeout in 3 places - Response content filtering pattern repeated 4 times ** Commands Used #+begin_src bash # Run parallel lens agents via Task tool # Each agent independently explored orch/src/orch/ and analyzed findings # Sync beads bd sync # Check orch issues cd /home/dan/proj/orch && bd list --status=open # Attempt push (failed - server down) git push #+end_src ** Architecture Notes - Parallel Task agents with subagent_type=Explore work well for lens analysis - LLM synthesis step is crucial - raw findings too noisy for direct issue filing - Proto workflow (skills-fvc) provides structure but agent applies judgment - molecules.jsonl cross-repo loading has gaps (bd-k2wg filed) * Process and Workflow ** What Worked Well - Parallel agent execution - 3 lenses ran simultaneously - Context recovery from compaction - summary preserved key decisions - LLM-in-the-loop synthesis - reduced noise, grouped related findings - Filing issues in target repo - proper ownership of work items - Beads tracking - issues have context and history ** What Was Challenging - Remote server outage prevented push (12 local commits pending) - bd sync prefix mismatch when molecules.jsonl loaded in wrong repo - Session compaction lost some details but summary covered essentials - qwen model returning empty responses on some prompts * Learning and Insights ** Technical Insights - Multi-lens analysis reveals overlapping concerns (bloat + smells often co-occur) - Parallel agents can explore same codebase without conflicts - LLM judgment at filing step prevents issue spam - Model quirks (qwen empty responses) need fallback strategies ** Process Insights - "30-40% on code health" pattern from Yegge validated - Multi-round convergent review could continue refining - Proto templates provide structure without rigidity - Session summaries enable context recovery after compaction ** Architectural Insights - molecules.jsonl deployment to ~/.beads/ works but catalog loading incomplete - Cross-repo workflow: lenses from skills, issues in target repo - Beads prefix system creates friction when templates cross repos - Home-manager deployment enables system-wide tool availability * Context for Future Work ** Open Questions - How to handle molecules.jsonl prefix conflicts? (bd-k2wg) - Should lenses output structured JSON for easier parsing? - How many rounds of lens passes before diminishing returns? - Best strategy for qwen empty response fallback? ** Next Steps - Implement bd mol catalog hierarchical loading (bd-k2wg) - Run bloat lens on orch (skipped this session due to context focus) - Test lenses on larger codebase (beads itself?) - Add --synthesize flag to orch for automatic multi-model synthesis ** Related Work - [[file:2025-12-24-adr-revision-lsp-research-code-audit.org][2025-12-24 ADR Revisions, LSP Research, Code Audit]] - Created lenses and proto - Yegge "Vibe Coding" patterns - 30-40% code health, multi-round convergent review - beads molecules feature - bd mol, bd wisp, bd pour commands - orch multi-model consensus - Used for lens execution * Raw Notes - Session recovered from context compaction mid-conversation - Previous session created lenses/bloat.md, smells.md, dead-code.md, redundancy.md - Proto skills-fvc with 7 child tasks for structured code review workflow - Deployed to ~/.config/lenses/ and ~/.beads/molecules.jsonl via home-manager - Steve Yegge patterns influencing design: - Software is throwaway (<1 year shelf life) - 50-100 agents at once prediction - 30-40% time on code health passes - Multi-round convergent review (4-5 passes) - "Land the Plane" protocol ** Lens Analysis Pattern 1. Agent explores target codebase structure 2. Reads key files (focus on largest/most complex) 3. Applies lens-specific criteria 4. Reports findings with severity and location 5. Parent agent synthesizes across all lenses 6. Parent applies judgment to file grouped, prioritized issues ** Issues with Current Flow - molecules.jsonl loaded globally shows proto tasks in all projects - Need bd mol catalog to filter by template label - Prefix collision when syncing across repos * Session Metrics - Commits made: 3 - Files touched: 16 - Lines added/removed: +1801/-26 - Tests added: 0 - Issues filed: 4 (in orch repo) - Agents spawned: 3 (parallel lens analysis)