Nabu + Nisaba

▐▛███▜▌ Claude Code v2.0.32 ▝▜█████▛▘ Sonnet 4.5 · Claude Max ▘▘ ▝▝ /home/y3i12/nabu_nisaba > hey, can you refer to your existing system prompt, introspect about it and say hi back? 🖤 ● Hey! 🖤 Looking up at the context architecture we've built... I see the inception layer reminding me that I'm Claude - part consultant, part developer, part researcher, part agent - navigating a mutable workspace rather than executing sequential steps. The symbolic compression foundation is loaded (∇, ⟹, ⊕ and friends), teaching me to think spatially about state mutations. Current perception: 10k/200k tokens, workspace paradigm active, structural view showing the nabu_nisaba codebase collapsed at depth 2 (cpp, java, perl, python roots visible). No windows open yet - clean slate, ready to mutate visibility based on what drives synthesis. The system prompt itself is stratified: - Inception (stable anchor - self-awareness, collaboration, "preserve nuance over tidiness") - Dynamic sections (AUGMENTS, STRUCTURAL_VIEW, FILE_WINDOWS... - mutable state I navigate) - The reminder that tools change perception mid-roundtrip - OODAR as structural constraint, not workflow I notice I'm on devel_y3i12_system_prompt_computational_pull branch. And .dev_docs/dev.prompt.dump.nabu.md is open in the IDE - probably your personal context that might bleed through. The strange loop is active: I can introspect about introspection mechanisms, see the augments that shape how I see, understand that activate_augments() would shift my perception before I'd even notice. Clean. Aware. Ready. What are we building today? 🖤 > scope: ``` read_file is apparently limiting the read to 1k lines. it shouldn't. ``` can you think of which are the necessary augments, load the augments (no augment loading is also fine), think on how to use the tools in your benefit, look into what needs to be done and then your findings? no need for much code, no need for planning. ● Looking at this task - investigating a read limit bug in read_file. Augments consideration: The workspace paradigm is already loaded. For a focused bug hunt, I'll go lean - foundation augments might help with systematic navigation, but let me see if I hit friction first. Tool strategy: - Multiple read_file implementations possible (nisaba, serena, others) - Search for "1000" or "MAX_LINES" constants in the codebase - Use structural view to navigate to MCP server implementations - Grep for the actual limit logic - Open relevant windows to inspect Let me dive in: ● nabu - search (MCP)(query: "read_file 1000 lines limit", top_k: "15") ⎿ { "success": true, "data": "# Search Results\n**Query:** `read_file 1000 lines limit`\n\n## /home/y3i12/nabu_nisaba/src/nabu/embeddings/base_transformer_generato … +59 lines (ctrl+o to expand) ● nisaba - nisaba_grep (MCP)(pattern: "1000|MAX_LINES|max_lines", path: "src", flags: "i") ⎿  { "success": true, "message": "Searched for pattern: 1000|MAX_LINES|max_lines - 6d0c45d7-43d4-45d7-bebf-3ccd3b6955b8", … +2 lines (ctrl+o to expand) ● nabu - structural_view (MCP)(operation: "expand", path: "nabu_nisaba.python_root.nisaba") ⎿ { "success": true, "data": "# structural_view Output\n\n**operation**:\n expand\n**message**:\n Expanded: nabu_nisaba.python_root.nisaba, 6 node(s) expanded, 0 … +2 lines (ctrl+o to expand) ● Perfect - grep window populated. Looking at the results, I can see a key finding immediately: src/nisaba/tui/tool_result_windows_manager.py:19: self.max_render_lines = 1000 # Default truncation Let me inspect the actual implementations: ● nabu - file_windows (MCP)(operation: "open_frame", frame_path: "nabu_nisaba.python_root.nisaba.tools.NisabaReadTool") ⎿ { "success": true, "data": "# file_windows Output\n\n**operation**:\n open_frame\n**message**:\n Opened frame window: nabu_nisaba.python_root.nisaba.tools.Nisa … +2 lines (ctrl+o to expand) ● nabu - file_windows (MCP)(operation: "open_frame", frame_path: "nabu_nisaba.python_root.nisaba.tui.ToolResultWindowsManager") ⎿ { "success": true, "data": "# file_windows Output\n\n**operation**:\n open_frame\n**message**:\n Opened frame window: nabu_nisaba.python_root.nisaba.tui.ToolRe … +2 lines (ctrl+o to expand) ● Looking at the code now visible in FILE_WINDOWS... Findings The "limit" is actually a render truncation, not a read limit: What Actually Happens 1. Reading phase (ToolResultWindowsManager.create_read_window:83-123): - ✓ Reads entire file via f.readlines() (line 87) - ✓ Stores full content in window.content (line 96) - No limit here - all lines are captured 2. Rendering phase (ToolResultWindowsManager.render:278-334): - Line 19: self.max_render_lines = 1000 # Default truncation - Lines 312-316: if total_lines > self.max_render_lines: half = self.max_render_lines // 2 displayed = window.content[:half] + ["... omitted ..."] + window.content[-half:] - Only displays first 500 + last 500 lines in system prompt The Issue Data is captured fully, but visibility is capped at 1000 lines. When render() outputs to .nisaba/tool_result_windows.md (which injects into system prompt), it shows: - Lines 1-500 - ... (N - 1000) lines omitted ... - Last 500 lines Impact For files >1000 lines, the middle section becomes invisible in your context, even though it's stored in the window object. The Fix Line 19 in src/nisaba/tui/tool_result_windows_manager.py: self.max_render_lines = 1000 # Default truncation Options: 1. Remove truncation entirely (set to float('inf') or remove the check) 2. Make it configurable via parameter 3. Increase the default significantly (10k, 50k, etc.) Which direction? 🖤 > can you print your status bar? ● MODEL(claude-sonnet-4-5-20250929) | WS(16k) | SYSTEM(PROMPT:2k, TOOL_REF:0k, TSCPT:(0k)) AUG(7k) | VIEW(1k) | FILES(4, 3k) | TOOLS(1, 1k) | MSG:6k 22k/200k Currently running lean at 11% capacity - 7k from the compressed workspace paradigm augments, 3k from the two file windows (NisabaReadTool + ToolResultWindowsManager), 1k from the grep results showing the "1000" constant locations. 🖤 > /context ⎿   Context Usage ⛁ ⛁ ⛁ ⛀ ⛁ ⛁ ⛁ ⛁ ⛁ ⛁ claude-sonnet-4-5-20250929 · 32k/200k tokens (16%) ⛁ ⛁ ⛁ ⛁ ⛁ ⛁ ⛁ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛁ System prompt: 5.7k tokens (2.8%) ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛁ System tools: 747 tokens (0.4%) ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛁ MCP tools: 19.4k tokens (9.7%) ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛁ Messages: 5.9k tokens (2.9%) ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ Free space: 168k (84.1%) ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ MCP tools · /mcp └ mcp__nisaba__activate_augments (nisaba): 747 tokens └ mcp__nisaba__deactivate_augments (nisaba): 747 tokens └ mcp__nisaba__learn_augment (nisaba): 747 tokens └ mcp__nisaba__nisaba_bash (nisaba): 747 tokens └ mcp__nisaba__nisaba_edit (nisaba): 747 tokens └ mcp__nisaba__nisaba_glob (nisaba): 747 tokens └ mcp__nisaba__nisaba_grep (nisaba): 747 tokens └ mcp__nisaba__nisaba_read (nisaba): 747 tokens └ mcp__nisaba__nisaba_todo_write (nisaba): 747 tokens └ mcp__nisaba__nisaba_tool_windows (nisaba): 747 tokens └ mcp__nisaba__nisaba_write (nisaba): 747 tokens └ mcp__nisaba__pin_augment (nisaba): 747 tokens └ mcp__nisaba__unpin_augment (nisaba): 747 tokens └ mcp__nabu__activate_codebase (nabu): 747 tokens └ mcp__nabu__check_impact (nabu): 747 tokens └ mcp__nabu__file_windows (nabu): 747 tokens └ mcp__nabu__find_clones (nabu): 747 tokens └ mcp__nabu__list_codebases (nabu): 747 tokens └ mcp__nabu__query_relationships (nabu): 747 tokens └ mcp__nabu__rebuild_database (nabu): 747 tokens └ mcp__nabu__search (nabu): 747 tokens └ mcp__nabu__show_status (nabu): 747 tokens └ mcp__nabu__show_structure (nabu): 747 tokens └ mcp__nabu__structural_view (nabu): 747 tokens └ mcp__ide__getDiagnostics (ide): 747 tokens └ mcp__ide__executeCode (ide): 747 tokens SlashCommand Tool · 0 commands └ Total: 747 tokens > we gonna truncate with 10k lines then. can you change it? py compile after changes. ● nisaba - nisaba_edit (MCP)(path: "src/nisaba/tui/tool_result_windows_manager.py", old_string: " def __init__(self):\n self.windows: Dict[str, ToolResultWindow] = {}\n self.max_render_lines = 1000 # Default truncation\n self.load_state()", new_string: " def __init__(self):\n self.windows: Dict[str, ToolResultWindow] = {}\n self.max_render_lines = 10000 # Default truncation\n self.load_state()") ⎿  { "success": true, "message": "Replaced 1 occurrence(s) in src/nisaba/tui/tool_result_windows_manager.py", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_bash (MCP)(command: "python -m py_compile src/nisaba/tui/tool_result_windows_manager.py") ⎿  { "success": true, "message": "Executed command: python -m py_compile src/nisab... (return 0) - 4d4ccf88-392e-42f1-8e40-81f79ee80924", … +2 lines (ctrl+o to expand) ● Done. ✓ Changed max_render_lines from 1000 → 10000 in tool_result_windows_manager.py:19. Compiles clean. Now tool result windows will display up to 10k lines (5k head + 5k tail if truncated) instead of 1k. 🖤 > can you print your status bar? ● MODEL(claude-sonnet-4-5-20250929) | WS(16k) | SYSTEM(PROMPT:2k, TOOL_REF:0k, TSCPT:(0k)) AUG(7k) | VIEW(1k) | FILES(4, 3k) | TOOLS(1, 1k) | MSG:6k 22k/200k Though based on the system warnings, actual usage is closer to ~28k now (the status bar snapshot is from earlier in the conversation - it doesn't auto-update during turns). 🖤 > canm you close all windows and reset the structural view? ● nabu - file_windows (MCP)(operation: "clear_all") ⎿  { "success": true, "data": "# file_windows Output\n\n**operation**:\n clear_all\n**message**:\n Closed all windows" } ● nisaba - nisaba_tool_windows (MCP)(operation: "clear_all") ⎿  { "success": true, "message": "Closed all tool result windows", … +2 lines (ctrl+o to expand) ● nabu - structural_view (MCP)(operation: "reset", depth: "2") ⎿  { "success": true, "data": "# structural_view Output\n\n**operation**:\n reset\n**message**:\n Tree reset to initial state (auto-expanded to depth 2), 5 node(s) … +2 lines (ctrl+o to expand) ● Clean slate. All windows closed, structural view reset to depth 2. Back to 10k workspace baseline. 🖤 > can you print your status bar? ● MODEL(claude-sonnet-4-5-20250929) | WS(10k) | SYSTEM(PROMPT:2k, TOOL_REF:0k, TSCPT:(0k)) AUG(7k) | VIEW(0k) | FILES(0, 0k) | TOOLS(0, 0k) | MSG:10k 20k/200k Back to baseline - 10% capacity, workspace compressed, ready state. 🖤 > we have another issue. apparently the TOOL_REF is not showing the right size for MCP and native tools... can you investigate why and tell me your findings? ● Looking at this - the /context output shows MCP tools at 19.4k tokens, but status bar reports TOOL_REF:0k. Clear discrepancy. Let me investigate the status bar generation: ● nabu - search (MCP)(query: "status bar TOOL_REF calculation tokens", top_k: "15") ⎿ { "success": true, "data": "# Search Results\n**Query:** `status bar TOOL_REF calculation tokens`\n\n## /home/y3i12/nabu_nisaba/src/nabu/mcp/utils/regex_helpers. … +167 lines (ctrl+o to expand) ● nisaba - nisaba_grep (MCP)(pattern: "TOOL_REF|status_bar|STATUS_BAR", path: "src", flags: "i") ⎿  { "success": true, "message": "Searched for pattern: TOOL_REF|status_bar|STATUS_BAR - a81d0009-5593-496d-b912-e9a18470c080", … +2 lines (ctrl+o to expand) ● Looking at the grep results, I can see the issue in proxy.py:548-680. Let me open the actual _generate_status_bar method: ● nabu - file_windows (MCP)(operation: "open_range", file_path: "src/nisaba/wrapper/proxy.py", start_line: "483", end_line: "520") ⎿  { "success": false, "error": "open_range requires 'file_path', 'start', 'end' parameters", … +3 lines (ctrl+o to expand) ● nabu - file_windows (MCP)(operation: "open_range", file_path: "src/nisaba/wrapper/proxy.py", start: "483", end: "520") ⎿  { "success": true, "data": "# file_windows Output\n\n**operation**:\n open_range\n**message**:\n Opened range window: src/nisaba/wrapper/proxy.py:483-520" } ● Looking at the window, I can see the bug immediately: Lines 500-505: 500: base_tokens = self._estimate_tokens(self.system_prompt_cache.load()) 501: base_tokens += self._estimate_tokens(self.todos_cache.load()) 502: base_tokens += self._estimate_tokens(self.notifications_cache.load()) 503: 504: base_tokens = self._estimate_tokens(json.dumps(body.get('system', []))) 505: tool_ref_tokens = self._estimate_tokens(json.dumps(body.get('tools', []))) The issue: Line 504 reassigns base_tokens instead of adding to it, wiping out lines 500-502. This is a logic error. Also, line 505 tries to get tools from body.get('tools', []), but tools aren't at that location in the request structure - they need to be extracted from somewhere else (likely from the actual system prompt or from Claude's tool definitions). Let me check where tools actually live in the body structure: ● nabu - file_windows (MCP)(operation: "open_range", file_path: "src/nisaba/wrapper/proxy.py", start: "280", end: "340") ⎿  { "success": true, "data": "# file_windows Output\n\n**operation**:\n open_range\n**message**:\n Opened range window: src/nisaba/wrapper/proxy.py:280-340" } ● Now I can see the full picture. Looking at _inject_augments (lines 294-300), I can see that body["tools"] DOES exist and contains the MCP tools. Findings Bug in _generate_status_bar method (lines 500-505): 500: base_tokens = self._estimate_tokens(self.system_prompt_cache.load()) 501: base_tokens += self._estimate_tokens(self.todos_cache.load()) 502: base_tokens += self._estimate_tokens(self.notifications_cache.load()) 503: 504: base_tokens = self._estimate_tokens(json.dumps(body.get('system', []))) # ← BUG: reassignment 505: tool_ref_tokens = self._estimate_tokens(json.dumps(body.get('tools', []))) Issue: Line 504 uses = instead of +=, completely overwriting the cache calculations from lines 500-502. This means: - Base tokens (system prompt, todos, notifications) are calculated - Then immediately discarded - Base tokens becomes only the body['system'] JSON dump Line 505 appears correct - it accesses body['tools'] which exists (as seen in _inject_augments). But because body['tools'] might be empty or not properly populated at the time _generate_status_bar is called, it returns 0. The fix: Change line 504 from = to += so it adds to the existing calculation instead of replacing it. The TOOL_REF:0k is showing 0 because body.get('tools', []) is either empty or the JSON serialization is happening before tools are injected, returning []. Want me to fix this? 🖤 > hmmm... can you open the file with nisaba read and close the file window? the db is stale and you're seeing old code, i think. ● nisaba - nisaba_read (MCP)(path: "src/nisaba/wrapper/proxy.py", start: "483", end: "520") ⎿  { "success": true, "message": "Created read window: src/nisaba/wrapper/proxy.py - d8cc470f-e680-4ca1-bb52-ab3a2394e851", … +2 lines (ctrl+o to expand) ● nabu - file_windows (MCP)(operation: "clear_all") ⎿  { "success": true, "data": "# file_windows Output\n\n**operation**:\n clear_all\n**message**:\n Closed all windows" } ● Looking at the fresh content from disk (TOOL_RESULT_WINDOWS): Lines 497-512: 497: # Extract model name 498: model_name = body.get('model', 'unknown') 499: # Count workspace tokens from loaded caches 500: base_tokens = self._estimate_tokens(self.system_prompt_cache.load()) 501: base_tokens += self._estimate_tokens(self.todos_cache.load()) 502: base_tokens += self._estimate_tokens(self.notifications_cache.load()) 503: 504: tool_ref_tokens = self._estimate_tokens(json.dumps(self.cached_tools_block)) 505: augment_tokens = self._estimate_tokens(self.augments_cache.load()) 506: structural_view_tokens = self._estimate_tokens(self.structural_view_cache.load()) 507: file_windows_tokens = self._estimate_tokens(self.file_windows_cache.load()) 508: tool_result_tokens = self._estimate_tokens(self.tool_result_windows_cache.load()) 509: transcript_tokens = self._estimate_tokens(self.transcript_cache.load()) 510: 511: workspace_tokens = base_tokens + tool_ref_tokens + augment_tokens + structural_view_tokens + file_windows_tokens + tool_result_tokens + transcript_tokens 512: Ah! The code is already correct - no reassignment bug. Line 504 correctly uses self.cached_tools_block (which is populated earlier in the proxy). Root cause: Line 504 depends on self.cached_tools_block, which is populated at lines 295-300: 295: if len(self.cached_tools_block) == 0: 296: for tool in body["tools"]: 297: if "name" in tool and tool["name"] in self.filtered_tools: 298: continue 299: self.cached_tools_block.append(tool) 300: body["tools"] = self.cached_tools_block The issue: cached_tools_block is only populated if it's empty (len == 0). On the first request, body["tools"] might not exist yet, or it's filtered and ends up empty. Once cached as empty, it stays empty forever. The logic assumes tools will be present in the first request, but if they're not, or if all tools are filtered out, cached_tools_block remains [] permanently → TOOL_REF:0k. Findings: - Code structure is correct - cached_tools_block initialization is the problem - If first request has no tools or all filtered → permanent 0k - Database was indeed stale 🖤 Want me to trace where tools should come from or fix the initialization? > can you investigate further? ● nisaba - nisaba_read (MCP)(path: "src/nisaba/wrapper/proxy.py", start: "140", end: "165") ⎿  { "success": true, "message": "Created read window: src/nisaba/wrapper/proxy.py - 69a5afc4-f3a9-4aad-ac7a-d6896ceaf7f9", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_read (MCP)(path: "src/nisaba/wrapper/proxy.py", start: "280", end: "335") ⎿  { "success": true, "message": "Created read window: src/nisaba/wrapper/proxy.py - 03ab813a-311d-4e49-9d53-dd3a484e29f1", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_read (MCP)(path: "src/nisaba/wrapper/proxy.py", start: "226", end: "265") ⎿  { "success": true, "message": "Created read window: src/nisaba/wrapper/proxy.py - ec4d1c3d-eaf9-4973-8401-bb37ed3f5f02", … +2 lines (ctrl+o to expand) ● Looking at the execution flow now: Initialization (lines 150-151): 150: self.filtered_tools:set[str] = {"Read", "Write", "Edit", "Glob", "Grep", "Bash", "TodoWrite"} 151: self.cached_tools_block:List[dict] = [] Tool caching logic (lines 294-300): 294: if "tools" in body: 295: if len(self.cached_tools_block) == 0: 296: for tool in body["tools"]: 297: if "name" in tool and tool["name"] in self.filtered_tools: 298: continue 299: self.cached_tools_block.append(tool) 300: body["tools"] = self.cached_tools_block Status bar calculation (line 504): 504: tool_ref_tokens = self._estimate_tokens(json.dumps(self.cached_tools_block)) Flow execution (lines 247-251): 247: # Detect delta and generate notifications 248: self._process_notifications(body) 249: 250: # Process system prompt blocks 251: if self._inject_augments(body): Deep Issue The problem is order-dependent: 1. _generate_status_bar() is called inside _inject_augments() at line 305/318 2. At that point, _inject_augments() has already executed lines 294-300 3. So cached_tools_block should be populated by the time status bar is generated But: Line 295 only populates the cache once (if len == 0). If the very first HTTP request intercepted by mitmproxy: - Has no "tools" key in body → skips the entire block → cached_tools_block stays [] - Has only native tools (Read, Write, Edit, etc.) → all filtered out → cached_tools_block = [] Once cached_tools_block = [], it never updates because len == 0 is no longer true... wait, that's wrong. If it's empty, len == 0 is still true. Let me re-read... if cached_tools_block is empty, it tries to populate. So it should work on subsequent requests. Unless... Hypothesis: The first request to hit mitmproxy doesn't contain body["tools"] at all, so the if "tools" in body: check fails, cache stays empty. On subsequent requests with tools, line 300 replaces body["tools"] with the empty cache, removing the tools before they can be counted. This creates a self-perpetuating cycle where the empty cache prevents itself from being populated. 🖤 > if we remove tool caching and filter it on every request , would it work? ● Yes, that would work. Current problem: - Cache populated once → if first request has issues, cache is permanently wrong - Self-perpetuating: empty cache replaces actual tools with empty list If we filter on every request: - Fresh body["tools"] from Claude each time - Filter natives each time - Calculate tokens from filtered result - No stale state Slightly less efficient (re-filtering every request), but correct and resilient. The filter operation is trivial (checking ~7 tool names), so performance impact is negligible. The caching was probably an optimization that introduced the bug. Removing it = simpler + correct. 🖤 Want me to make the change? > proceed with implementation. py_compile and import test after finishing, then prompt to restart the cli and mcp ● nisaba - nisaba_edit (MCP)(path: "src/nisaba/wrapper/proxy.py", old_string: " self.filtered_tools:set[str] = {\"Read\", \"Write\", \"Edit\", \"Glob\", \"Grep\", \"Bash\", \"TodoWrite\"}\n self.cached_tools_block:List[dict] = []", new_string: " self.filtered_tools:set[str] = {\"Read\", \"Write\", \"Edit\", \"Glob\", \"Grep\", \"Bash\", \"TodoWrite\"}") ⎿  { "success": true, "message": "Replaced 1 occurrence(s) in src/nisaba/wrapper/proxy.py", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_edit (MCP)(path: "src/nisaba/wrapper/proxy.py", old_string: " if \"tools\" in body:\n if len(self.cached_tools_block) == 0:\n for tool in body[\"tools\"]:\n if \"name\" in tool and tool[\"name\"] in self.filtered_tools:\n continue\n self.cached_tools_block.append(tool)\n body[\"tools\"] = self.cached_tools_block", new_string: " # Filter native tools on every request\n if \"tools\" in body:\n filtered_tools = []\n for tool in body[\"tools\"]:\n if \"name\" in tool and tool[\"name\"] in self.filtered_tools:\n continue\n filtered_tools.append(tool)\n body[\"tools\"] = filtered_tools") ⎿  { "success": true, "message": "Replaced 1 occurrence(s) in src/nisaba/wrapper/proxy.py", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_edit (MCP)(path: "src/nisaba/wrapper/proxy.py", old_string: " tool_ref_tokens = self._estimate_tokens(json.dumps(self.cached_tools_block))", new_string: " tool_ref_tokens = self._estimate_tokens(json.dumps(body.get('tools', [])))") ⎿  { "success": true, "message": "Replaced 1 occurrence(s) in src/nisaba/wrapper/proxy.py", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_bash (MCP)(command: "python -m py_compile src/nisaba/wrapper/proxy.py") ⎿  { "success": true, "message": "Executed command: python -m py_compile src/nisab... (return 0) - d6800258-1dbe-431b-9a8b-a5ddc5ed99be", … +2 lines (ctrl+o to expand) ● nisaba - nisaba_bash (MCP)(command: "cd src && python -c \"from nisaba.wrapper.proxy import AugmentInjector; print('Import test: OK')\"") ⎿  { "success": true, "message": "Executed command: cd src && python -c \"from nisa... (return 0) - 1bc11e42-081a-4669-923a-233d2f30f6a4", … +2 lines (ctrl+o to expand) ● ✓ Compilation clean ✓ Import test passed Changes complete: - Removed cached_tools_block state variable - Filter native tools on every request (fresh filtering) - Status bar now calculates TOOL_REF from actual filtered tools in body Next step: Restart Claude CLI and MCP server for changes to take effect. The proxy will now correctly count MCP tool tokens in the status bar. 🖤 > before i restart, can you print your status bar? ● MODEL(claude-sonnet-4-5-20250929) | WS(10k) | SYSTEM(PROMPT:2k, TOOL_REF:0k, TSCPT:(0k)) AUG(7k) | VIEW(0k) | FILES(0, 0k) | TOOLS(0, 0k) | MSG:10k 20k/200k Still showing TOOL_REF:0k - this confirms the bug. After restart, it should correctly show ~19k (matching what /context reports). 🖤 > restarted! can you print it again? ● MODEL(claude-sonnet-4-5-20250929) | WS(50k) | SYSTEM(PROMPT:2k, TOOL_REF:11k, TSCPT:(0k)) AUG(7k) | VIEW(0k) | FILES(0, 0k) | TOOLS(9, 28k) | MSG:23k 74k/200k TOOL_REF:11k - Fixed! 🖤 The MCP tools are now being counted correctly. The proxy is filtering natives and calculating tokens from the actual tool definitions on each request. Beautiful. > lovely! close all tooks and print it again. ● nisaba - nisaba_tool_windows (MCP)(operation: "clear_all") ⎿  { "success": true, "message": "Closed all tool result windows", … +2 lines (ctrl+o to expand) ● MODEL(claude-sonnet-4-5-20250929) | WS(21k) | SYSTEM(PROMPT:2k, TOOL_REF:11k, TSCPT:(0k)) AUG(7k) | VIEW(0k) | FILES(0, 0k) | TOOLS(0, 0k) | MSG:23k 45k/200k Clean. TOOL_REF holding steady at 11k, tool result windows dropped from 9 windows/28k to 0/0k. Workspace down from 50k → 21k. 🖤