tools-only Continuous Learning Log
Bugs, smells, issues dumped here as encountered. Raw is fine. A skill will organize this into proper kb entries later.
Format: [date] [type] description
Types: bug, smell, pattern, lesson, antipattern
[2026-01-07] [lesson] When there's a type mismatch between A and B, fix where A or B is defined, not every place that uses them. Don't scatter changes across 5+ files when one line at the source fixes everything.
[2026-01-08] [pattern] Local mode config: docs/configuration/tunacode.local.json.example - use when running local models. Key settings: local_mode: true, local_max_tokens: 1000, context_window_size: 10000, OPENAI_BASE_URL for local server.
[2026-01-08] [pattern] Syntax highlighting in tool renderers: Use syntax_utils.py for get_lexer(filepath) and syntax_or_text(content, filepath). Consistent monokai theme. 9 renderers now registered: bash, glob, grep, list_dir, read_file, research_codebase, update_file, web_fetch, write_file. Commit 9db8e92.
[2026-01-08] [antipattern] RichLog.write(expand=True) is NOT terminal width! expand=True expands to scrollable_content_region, which excludes padding and scrollbar gutter (~4-8 chars narrower than terminal). For full-width panels, pass explicit width= to the Panel constructor. Never trust expand=True to mean "full width" - it means "fill container" and the container is smaller than you think. See Gate 5: Indirection Requires Verification.
[2026-01-14] [antipattern] Semantically dead code: loaded but never read. Static analysis (Vulture) only catches syntactically dead code (never called). It misses code that IS called but whose result is never consumed. Example: glob.py had _load_gitignore_patterns() that populated a global, but nothing ever read that global. The use_gitignore parameter was a lie - it triggered work but had zero effect. Prevention: When adding a "load X" function, grep for reads of X before shipping. If a parameter controls behavior, trace the data flow to prove it actually changes output.
[2026-01-17] [bug] Dangling tool calls on user abort (PR #246). User aborts mid-tool-call → messages has ModelResponse with tool calls but no ToolReturn → next API request fails. Root cause: exception path violated message invariant (every tool call needs a return). Fix: _remove_dangling_tool_calls() in except UserAbortError. Prevention: Document state invariants. Test exception scenarios. See Gate 6.
[2026-01-24] [bug] Shallow copy corrupts DEFAULT_USER_CONFIG. .copy() is shallow - nested dicts (settings, env) still reference the constant. Setup was mutating user_config in-place → polluted module-level default → first-run config missing all defaults. Fix: Don't mutate, replace. state.py assigns constant directly (reference replaced by setup). setup.py builds new dict from deepcopy(DEFAULT_USER_CONFIG). Key insight: If you don't mutate, you don't need to copy. See .claude/JOURNAL.md 2026-01-24 entry.
[2026-01-25] [pattern] Canonical messaging adoption complete (Task 01). Migrated production code to use adapter.get_content() (P1) and routed sanitize.py through adapter helpers (P2). Key insight: adapter layer now handles ALL message polymorphism. Detection uses adapter (find_dangling_tool_calls, get_tool_call_ids), mutation stays in sanitize.py. Deleted ~117 LOC of duplicate accessors. Branch: types-architect. See .claude/JOURNAL.md 2026-01-25 entry.
[2026-01-25] [bug] Orphaned retry-prompt parts after dangling tool call cleanup. When pruning dangling tool calls, _filter_dangling_tool_calls_from_parts() only removed tool-call parts. This left behind retry-prompt parts (pydantic-ai's error response for failed tools like 403). Fix: Filter ANY part with tool_call_id matching a dangling ID, not just part_kind == "tool-call". Key insight: pydantic-ai uses multiple part kinds (tool-call, tool-return, retry-prompt) that all reference the same tool_call_id. Cleanup must be ID-based, not kind-based.