update docs

This reverts commit 1581380a43.

MainContext.md

@@ -12,16 +12,16 @@ Is a local GUI tool for manually curating and sending context to AI APIs. It agg
 - `uv` - package/env management
 
 **Files:**
-- `gui.py` - main GUI, `App` class, all panels, all callbacks, confirmation dialog, layout persistence, rich comms rendering
-- `ai_client.py` - unified provider wrapper, model listing, session management, send, tool/function-call loop, comms log, provider error classification
-- `aggregate.py` - reads config, collects files/screenshots/discussion, writes numbered `.md` files to `output_dir`
+- `gui.py` - main GUI, `App` class, all panels, all callbacks, confirmation dialog, layout persistence, rich comms rendering; `[+ Maximize]` buttons in `ConfirmDialog` and `win_script_output` now pass text directly as `user_data` / read from `self._last_script` / `self._last_output` instance vars instead of `dpg.get_value(tag)` — fixes glitch when word-wrap is ON or dialog is dismissed before viewer opens
+- `ai_client.py` - unified provider wrapper, model listing, session management, send, tool/function-call loop, comms log, provider error classification, token estimation, and aggressive history truncation
+- `aggregate.py` - reads config, collects files/screenshots/discussion, builds `file_items` with `mtime` for cache optimization, writes numbered `.md` files to `output_dir` using `build_markdown_from_items` to avoid double I/O; `run()` returns `(markdown_str, path, file_items)` tuple; `summary_only=False` by default (full file contents sent, not heuristic summaries)
 - `shell_runner.py` - subprocess wrapper that runs PowerShell scripts sandboxed to `base_dir`, returns stdout/stderr/exit code as a string
 - `session_logger.py` - opens timestamped log files at session start; writes comms entries as JSON-L and tool calls as markdown; saves each AI-generated script as a `.ps1` file
 - `project_manager.py` - per-project .toml load/save, entry serialisation (entry_to_str/str_to_entry with @timestamp support), default_project/default_discussion factories, migrate_from_legacy_config, flat_config for aggregate.run(), git helpers (get_git_commit, get_git_log)
 - `theme.py` - palette definitions, font loading, scale, load_from_config/save_to_config
 - `gemini.py` - legacy standalone Gemini wrapper (not used by the main GUI; superseded by `ai_client.py`)
 - `file_cache.py` - stub; Anthropic Files API path removed; kept so stale imports don't break
-- `mcp_client.py` - MCP-style read-only file tools (read_file, list_directory, search_files, get_file_summary); allowlist enforced against project file_items + base_dirs; dispatched by ai_client tool-use loop for both Anthropic and Gemini
+- `mcp_client.py` - MCP-style tools (read_file, list_directory, search_files, get_file_summary, web_search, fetch_url); allowlist enforced against project file_items + base_dirs for file tools; web tools are unrestricted; dispatched by ai_client tool-use loop for both Anthropic and Gemini
 - `summarize.py` - local heuristic summariser (no AI); .py via AST, .toml via regex, .md headings, generic preview; used by mcp_client.get_file_summary and aggregate.build_summary_section
 - `config.toml` - global-only settings: [ai] provider+model+system_prompt, [theme] palette+font+scale, [projects] paths array + active path
 - `manual_slop.toml` - per-project file: [project] name+git_dir+system_prompt+main_context, [output] namespace+output_dir, [files] base_dir+paths, [screenshots] base_dir+paths, [discussion] roles+active+[discussion.discussions.<name>] git_commit+last_updated+history
@@ -87,7 +87,7 @@ Is a local GUI tool for manually curating and sending context to AI APIs. It agg
 - All tool calls (script + result/rejection) are appended to `_tool_log` and displayed in the Tool Calls panel
 
 **Dynamic file context refresh (ai_client.py):**
-- After the last tool call in each round, all project files from `file_items` are re-read from disk via `_reread_file_items()`. The `file_items` variable is reassigned so subsequent rounds see fresh content.
+- After the last tool call in each round, project files from `file_items` are checked via `_reread_file_items()`. It uses `mtime` to only re-read modified files, returning only the `changed` files to build a minimal `[FILES UPDATED]` block.
 - For Anthropic: the refreshed file contents are injected as a `text` block appended to the `tool_results` user message, prefixed with `[FILES UPDATED]` and an instruction not to re-read them.
 - For Gemini: refreshed file contents are appended to the last function response's `output` string as a `[SYSTEM: FILES UPDATED]` block. On the next tool round, stale `[FILES UPDATED]` blocks are stripped from history and old tool outputs are truncated to `_history_trunc_limit` characters to control token growth.
 - `_build_file_context_text(file_items)` formats the refreshed files as markdown code blocks (same format as the original context)
@@ -141,10 +141,12 @@ Entry layout: index + timestamp + direction + kind + provider/model header row,
 - `log_tool_call(script, result, script_path)` writes the script to `scripts/generated/<ts>_<seq:04d>.ps1` and appends a markdown record to the toolcalls log without the script body (just the file path + result); uses a `threading.Lock` for the sequence counter
 - `close_session()` flushes and closes both file handles; called just before `dpg.destroy_context()`
 
-**Anthropic prompt caching:**
+**Anthropic prompt caching & history management:**
 - System prompt + context are combined into one string, chunked into <=120k char blocks, and sent as the `system=` parameter array. Only the LAST chunk gets `cache_control: ephemeral`, so the entire system prefix is cached as one unit.
 - Last tool in `_ANTHROPIC_TOOLS` (`run_powershell`) has `cache_control: ephemeral`; this means the tools prefix is cached together with the system prefix after the first request.
 - The user message is sent as a plain `[{"type": "text", "text": user_message}]` block with NO cache_control. The context lives in `system=`, not in the first user message.
+- `_add_history_cache_breakpoint` places `cache_control:ephemeral` on the last content block of the second-to-last user message, using the 4th cache breakpoint to cache the conversation history prefix.
+- `_trim_anthropic_history` uses token estimation (`_CHARS_PER_TOKEN = 3.5`) to keep the prompt under `_ANTHROPIC_MAX_PROMPT_TOKENS = 180_000`. It strips stale file refreshes from old turns, and drops oldest turn pairs if still over budget.
 - The tools list is built once per session via `_get_anthropic_tools()` and reused across all API calls within the tool loop, avoiding redundant Python-side reconstruction.
 - `_strip_cache_controls()` removes stale `cache_control` markers from all history entries before each API call, ensuring only the stable system/tools prefix consumes cache breakpoint slots.
 - Cache stats (creation tokens, read tokens) are surfaced in the comms log usage dict and displayed in the Comms History panel
@@ -180,13 +182,15 @@ Entry layout: index + timestamp + direction + kind + provider/model header row,
 **MCP file tools (mcp_client.py + ai_client.py):**
 - Four read-only tools exposed to the AI as native function/tool declarations: `read_file`, `list_directory`, `search_files`, `get_file_summary`
 - Access control: `mcp_client.configure(file_items, extra_base_dirs)` is called before each send; builds an allowlist of resolved absolute paths from the project's `file_items` plus the `base_dir`; any path that is not explicitly in the list or not under one of the allowed directories returns `ACCESS DENIED`
-- `mcp_client.dispatch(tool_name, tool_input)` is the single dispatch entry point used by both Anthropic and Gemini tool-use loops
+- `mcp_client.dispatch(tool_name, tool_input)` is the single dispatch entry point used by both Anthropic and Gemini tool-use loops; `TOOL_NAMES` set now includes all six tool names
 - Anthropic: MCP tools appear before `run_powershell` in the tools list (no `cache_control` on them; only `run_powershell` carries `cache_control: ephemeral`)
 - Gemini: MCP tools are included in the `FunctionDeclaration` list alongside `run_powershell`
 - `get_file_summary` uses `summarize.summarise_file()` — same heuristic used for the initial `<context>` block, so the AI gets the same compact structural view it already knows
 - `list_directory` sorts dirs before files; shows name, type, and size
 - `search_files` uses `Path.glob()` with the caller-supplied pattern (supports `**/*.py` style)
 - `read_file` returns raw UTF-8 text; errors (not found, access denied, decode error) are returned as error strings rather than exceptions, so the AI sees them as tool results
+- `web_search(query)` queries DuckDuckGo HTML endpoint and returns the top 5 results (title, URL, snippet) as a formatted string; uses a custom `_DDGParser` (HTMLParser subclass)
+- `fetch_url(url)` fetches a URL, strips HTML tags/scripts via `_TextExtractor` (HTMLParser subclass), collapses whitespace, and truncates to 40k chars to prevent context blowup; handles DuckDuckGo redirect links automatically
 - `summarize.py` heuristics: `.py` → AST imports + ALL_CAPS constants + classes+methods + top-level functions; `.toml` → table headers + top-level keys; `.md` → h1–h3 headings with indentation; all others → line count + first 8 lines preview
 - Comms log: MCP tool calls log `OUT/tool_call` with `{"name": ..., "args": {...}}` and `IN/tool_result` with `{"name": ..., "output": ...}`; rendered in the Comms History panel via `_render_payload_tool_call` (shows each arg key/value) and `_render_payload_tool_result` (shows output)
 
@@ -199,7 +203,9 @@ Entry layout: index + timestamp + direction + kind + provider/model header row,
 
 ### Gemini Context Management
 - Gemini uses explicit caching via `client.caches.create()` to store the `system_instruction` + tools as an immutable cached prefix with a 1-hour TTL. The cache is created once per chat session.
+- Proactively rebuilds cache at 90% of `_GEMINI_CACHE_TTL = 3600` to avoid stale-reference errors.
 - When context changes (detected via `md_content` hash), the old cache is deleted, a new cache is created, and chat history is migrated to a fresh chat session pointing at the new cache.
+- Trims history by dropping oldest pairs if input tokens exceed `_GEMINI_MAX_INPUT_TOKENS = 900_000`.
 - If cache creation fails (e.g., content is under the minimum token threshold — 1024 for Flash, 4096 for Pro), the system falls back to inline `system_instruction` in the chat config. Implicit caching may still provide cost savings in this case.
 - The `<context>` block lives inside `system_instruction`, NOT in user messages, preventing history bloat across turns.
 - On cleanup/exit, active caches are deleted via `ai_client.cleanup()` to prevent orphaned billing.
@@ -244,3 +250,34 @@ Documentation has been completely rewritten matching the strict, structural form
 - `docs/guide_architecture.md`: Details the Python implementation algorithms, queue management for UI rendering, the specific AST heuristics used for context aggregation, and the distinct algorithms for trimming Anthropic history vs Gemini state caching.
 - `docs/Readme.md`: The core interface manual.
 - `docs/guide_tools.md`: Security architecture for `_is_allowed` paths and definitions of the read-only vs destructive tool pipeline.
+
+
+
+
+## Updates (2026-02-22 — ai_client.py & aggregate.py)
+
+### mcp_client.py — Web Tools Added
+- `web_search(query)` and `fetch_url(url)` added as two new MCP tools alongside the existing four file tools.
+- `TOOL_NAMES` set updated to include all six tool names for dispatch routing.
+- `MCP_TOOL_SPECS` list extended with full JSON schema definitions for both web tools.
+- Both tools are declared in `_build_anthropic_tools()` and `_gemini_tool_declaration()` so they are available to both providers.
+- Web tools bypass the `_is_allowed` path check (no filesystem access); file tools retain the allowlist enforcement.
+
+### aggregate.py — run() double-I/O elimination
+- `run()` now calls `build_file_items()` once, then passes the result to `build_markdown_from_items()` instead of calling `build_files_section()` separately. This avoids reading every file twice per send.
+- `build_markdown_from_items()` accepts a `summary_only` flag (default `False`); when `False` it inlines full file content; when `True` it delegates to `summarize.build_summary_markdown()` for compact structural summaries.
+- `run()` returns a 3-tuple `(markdown_str, output_path, file_items)` — the `file_items` list is passed through to `gui.py` as `self.last_file_items` for dynamic context refresh after tool calls.
+
+
+## Updates (2026-02-22 — gui.py [+ Maximize] bug fix)
+
+### Problem
+Three `[+ Maximize]` buttons were reading their text content via `dpg.get_value(tag)` at click time:
+1. `ConfirmDialog.show()` — passed `f"{self._tag}_script"` as `user_data` and called `dpg.get_value(u)` in the lambda. If the dialog was dismissed before the viewer opened, the item no longer existed and the call would fail silently or crash.
+2. `win_script_output` Script `[+ Maximize]` — used `user_data="last_script_text"` and `dpg.get_value(u)`. When word-wrap is ON, `last_script_text` is hidden (`show=False`); in some DPG versions `dpg.get_value` on a hidden `input_text` returns `""`.
+3. `win_script_output` Output `[+ Maximize]` — same issue with `"last_script_output"`.
+
+### Fix
+- `ConfirmDialog.show()`: changed `user_data` to `self._script` (the actual text string captured at button-creation time) and the callback to `lambda s, a, u: _show_text_viewer("Confirm Script", u)`. The text is now baked in at dialog construction, not read from a potentially-deleted widget.
+- `App._append_tool_log()`: added `self._last_script = script` and `self._last_output = result` assignments so the latest values are always available as instance state.
+- `win_script_output` buttons: both `[+ Maximize]` buttons now use `lambda s, a, u: _show_text_viewer("...", self._last_script/output)` directly, bypassing DPG widget state entirely.

aggregate.py

@@ -98,24 +98,28 @@ def build_file_items(base_dir: Path, files: list[str]) -> list[dict]:
         entry    : str   (original config entry string)
         content  : str   (file text, or error string)
         error    : bool
+        mtime    : float (last modification time, for skip-if-unchanged optimization)
     """
     items = []
     for entry in files:
         paths = resolve_paths(base_dir, entry)
         if not paths:
-            items.append({"path": None, "entry": entry, "content": f"ERROR: no files matched: {entry}", "error": True})
+            items.append({"path": None, "entry": entry, "content": f"ERROR: no files matched: {entry}", "error": True, "mtime": 0.0})
             continue
         for path in paths:
             try:
                 content = path.read_text(encoding="utf-8")
+                mtime = path.stat().st_mtime
                 error = False
             except FileNotFoundError:
                 content = f"ERROR: file not found: {path}"
+                mtime = 0.0
                 error = True
             except Exception as e:
                 content = f"ERROR: {e}"
+                mtime = 0.0
                 error = True
-            items.append({"path": path, "entry": entry, "content": content, "error": error})
+            items.append({"path": path, "entry": entry, "content": content, "error": error, "mtime": mtime})
     return items
 
 def build_summary_section(base_dir: Path, files: list[str]) -> str:
@@ -126,6 +130,40 @@ def build_summary_section(base_dir: Path, files: list[str]) -> str:
     items = build_file_items(base_dir, files)
     return summarize.build_summary_markdown(items)
 
+def _build_files_section_from_items(file_items: list[dict]) -> str:
+    """Build the files markdown section from pre-read file items (avoids double I/O)."""
+    sections = []
+    for item in file_items:
+        path = item.get("path")
+        entry = item.get("entry", "unknown")
+        content = item.get("content", "")
+        if path is None:
+            sections.append(f"### `{entry}`\n\n```text\n{content}\n```")
+            continue
+        suffix = path.suffix.lstrip(".") if hasattr(path, "suffix") else "text"
+        lang = suffix if suffix else "text"
+        original = entry if "*" not in entry else str(path)
+        sections.append(f"### `{original}`\n\n```{lang}\n{content}\n```")
+    return "\n\n---\n\n".join(sections)
+
+
+def build_markdown_from_items(file_items: list[dict], screenshot_base_dir: Path, screenshots: list[str], history: list[str], summary_only: bool = False) -> str:
+    """Build markdown from pre-read file items instead of re-reading from disk."""
+    parts = []
+    # STATIC PREFIX: Files and Screenshots must go first to maximize Cache Hits
+    if file_items:
+        if summary_only:
+            parts.append("## Files (Summary)\n\n" + summarize.build_summary_markdown(file_items))
+        else:
+            parts.append("## Files\n\n" + _build_files_section_from_items(file_items))
+    if screenshots:
+        parts.append("## Screenshots\n\n" + build_screenshots_section(screenshot_base_dir, screenshots))
+    # DYNAMIC SUFFIX: History changes every turn, must go last
+    if history:
+        parts.append("## Discussion History\n\n" + build_discussion_section(history))
+    return "\n\n---\n\n".join(parts)
+
+
 def build_markdown(base_dir: Path, files: list[str], screenshot_base_dir: Path, screenshots: list[str], history: list[str], summary_only: bool = False) -> str:
     parts = []
     # STATIC PREFIX: Files and Screenshots must go first to maximize Cache Hits
@@ -141,7 +179,7 @@ def build_markdown(base_dir: Path, files: list[str], screenshot_base_dir: Path,
         parts.append("## Discussion History\n\n" + build_discussion_section(history))
     return "\n\n---\n\n".join(parts)
 
-def run(config: dict) -> tuple[str, Path]:
+def run(config: dict) -> tuple[str, Path, list[dict]]:
     namespace = config.get("project", {}).get("name")
     if not namespace:
         namespace = config.get("output", {}).get("namespace", "project")
@@ -155,11 +193,11 @@ def run(config: dict) -> tuple[str, Path]:
     output_dir.mkdir(parents=True, exist_ok=True)
     increment = find_next_increment(output_dir, namespace)
     output_file = output_dir / f"{namespace}_{increment:03d}.md"
-    # Provide full files to trigger Gemini's 32k cache threshold and give the AI immediate context
-    markdown = build_markdown(base_dir, files, screenshot_base_dir, screenshots, history,
+    # Build file items once, then construct markdown from them (avoids double I/O)
+    file_items = build_file_items(base_dir, files)
+    markdown = build_markdown_from_items(file_items, screenshot_base_dir, screenshots, history,
                                          summary_only=False)
     output_file.write_text(markdown, encoding="utf-8")
-    file_items = build_file_items(base_dir, files)
     return markdown, output_file, file_items
 
 def main():

ai_client.py

@@ -13,6 +13,7 @@ during chat creation to avoid massive history bloat.
 # ai_client.py
 import tomllib
 import json
+import time
 import datetime
 from pathlib import Path
 import file_cache
@@ -34,6 +35,12 @@ def set_model_params(temp: float, max_tok: int, trunc_limit: int = 8000):
 _gemini_client = None
 _gemini_chat = None
 _gemini_cache = None
+_gemini_cache_md_hash: int | None = None
+_gemini_cache_created_at: float | None = None
+
+# Gemini cache TTL in seconds. Caches are created with this TTL and
+# proactively rebuilt at 90% of this value to avoid stale-reference errors.
+_GEMINI_CACHE_TTL = 3600
 
 _anthropic_client = None
 _anthropic_history: list[dict] = []
@@ -216,6 +223,7 @@ def cleanup():
 
 def reset_session():
     global _gemini_client, _gemini_chat, _gemini_cache
+    global _gemini_cache_md_hash, _gemini_cache_created_at
     global _anthropic_client, _anthropic_history
     global _CACHED_ANTHROPIC_TOOLS
     if _gemini_client and _gemini_cache:
@@ -226,6 +234,8 @@ def reset_session():
     _gemini_client = None
     _gemini_chat = None
     _gemini_cache = None
+    _gemini_cache_md_hash = None
+    _gemini_cache_created_at = None
     _anthropic_client = None
     _anthropic_history = []
     _CACHED_ANTHROPIC_TOOLS = None
@@ -383,12 +393,15 @@ def _run_script(script: str, base_dir: str) -> str:
 
 # ------------------------------------------------------------------ dynamic file context refresh
 
-def _reread_file_items(file_items: list[dict]) -> list[dict]:
+def _reread_file_items(file_items: list[dict]) -> tuple[list[dict], list[dict]]:
     """
-    Re-read every file in file_items from disk, returning a fresh list.
-    This is called after tool calls so the AI sees updated file contents.
+    Re-read file_items from disk, but only files whose mtime has changed.
+    Returns (all_items, changed_items) — all_items is the full refreshed list,
+    changed_items contains only the files that were actually modified since
+    the last read (used to build a minimal [FILES UPDATED] block).
     """
     refreshed = []
+    changed = []
     for item in file_items:
         path = item.get("path")
         if path is None:
@@ -397,11 +410,20 @@ def _reread_file_items(file_items: list[dict]) -> list[dict]:
         from pathlib import Path as _P
         p = _P(path) if not isinstance(path, _P) else path
         try:
+            current_mtime = p.stat().st_mtime
+            prev_mtime = item.get("mtime", 0.0)
+            if current_mtime == prev_mtime:
+                refreshed.append(item)  # unchanged — skip re-read
+                continue
             content = p.read_text(encoding="utf-8")
-            refreshed.append({**item, "content": content, "error": False})
+            new_item = {**item, "content": content, "error": False, "mtime": current_mtime}
+            refreshed.append(new_item)
+            changed.append(new_item)
         except Exception as e:
-            refreshed.append({**item, "content": f"ERROR re-reading {p}: {e}", "error": True})
-    return refreshed
+            err_item = {**item, "content": f"ERROR re-reading {p}: {e}", "error": True, "mtime": 0.0}
+            refreshed.append(err_item)
+            changed.append(err_item)
+    return refreshed, changed
 
 
 def _build_file_context_text(file_items: list[dict]) -> str:
@@ -453,8 +475,20 @@ def _ensure_gemini_client():
         _gemini_client = genai.Client(api_key=creds["gemini"]["api_key"])
 
 
+
+def _get_gemini_history_list(chat):
+    if not chat: return []
+    # google-genai SDK stores the mutable list in _history
+    if hasattr(chat, "_history"):
+        return chat._history
+    if hasattr(chat, "history"):
+        return chat.history
+    if hasattr(chat, "get_history"):
+        return chat.get_history()
+    return []
+
 def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items: list[dict] | None = None) -> str:
-    global _gemini_chat, _gemini_cache
+    global _gemini_chat, _gemini_cache, _gemini_cache_md_hash, _gemini_cache_created_at
     from google.genai import types
     try:
         _ensure_gemini_client(); mcp_client.configure(file_items or [], [base_dir])
@@ -464,15 +498,29 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
         # DYNAMIC CONTEXT: Check if files/context changed mid-session
         current_md_hash = hash(md_content)
         old_history = None
-        if _gemini_chat and getattr(_gemini_chat, "_last_md_hash", None) != current_md_hash:
-            old_history = list(_gemini_chat.history) if _gemini_chat.history else []
+        if _gemini_chat and _gemini_cache_md_hash != current_md_hash:
+            old_history = list(_get_gemini_history_list(_gemini_chat)) if _get_gemini_history_list(_gemini_chat) else []
             if _gemini_cache:
                 try: _gemini_client.caches.delete(name=_gemini_cache.name)
                 except: pass
             _gemini_chat = None
             _gemini_cache = None
+            _gemini_cache_created_at = None
             _append_comms("OUT", "request", {"message": "[CONTEXT CHANGED] Rebuilding cache and chat session..."})
 
+        # CACHE TTL: Proactively rebuild before the cache expires server-side.
+        # If we don't, send_message() will reference a deleted cache and fail.
+        if _gemini_chat and _gemini_cache and _gemini_cache_created_at:
+            elapsed = time.time() - _gemini_cache_created_at
+            if elapsed > _GEMINI_CACHE_TTL * 0.9:
+                old_history = list(_get_gemini_history_list(_gemini_chat)) if _get_gemini_history_list(_gemini_chat) else []
+                try: _gemini_client.caches.delete(name=_gemini_cache.name)
+                except: pass
+                _gemini_chat = None
+                _gemini_cache = None
+                _gemini_cache_created_at = None
+                _append_comms("OUT", "request", {"message": f"[CACHE TTL] Rebuilding cache (expired after {int(elapsed)}s)..."})
+
         if not _gemini_chat:
             chat_config = types.GenerateContentConfig(
                 system_instruction=sys_instr,
@@ -488,9 +536,10 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                     config=types.CreateCachedContentConfig(
                         system_instruction=sys_instr,
                         tools=tools_decl,
-                        ttl="3600s",
+                        ttl=f"{_GEMINI_CACHE_TTL}s",
                     )
                 )
+                _gemini_cache_created_at = time.time()
                 chat_config = types.GenerateContentConfig(
                     cached_content=_gemini_cache.name,
                     temperature=_temperature,
@@ -499,22 +548,24 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                 )
                 _append_comms("OUT", "request", {"message": f"[CACHE CREATED] {_gemini_cache.name}"})
             except Exception as e:
-                _gemini_cache = None  # Ensure clean state on failure
+                _gemini_cache = None
+                _gemini_cache_created_at = None
+                _append_comms("OUT", "request", {"message": f"[CACHE FAILED] {type(e).__name__}: {e} — falling back to inline system_instruction"})
 
             kwargs = {"model": _model, "config": chat_config}
             if old_history:
                 kwargs["history"] = old_history
 
             _gemini_chat = _gemini_client.chats.create(**kwargs)
-            _gemini_chat._last_md_hash = current_md_hash
+            _gemini_cache_md_hash = current_md_hash
         
         _append_comms("OUT", "request", {"message": f"[ctx {len(md_content)} + msg {len(user_message)}]"})
         payload, all_text = user_message, []
 
-        for r_idx in range(MAX_TOOL_ROUNDS + 2):
-            # Strip stale file refreshes and truncate old tool outputs in Gemini history
-            if _gemini_chat and _gemini_chat.history:
-                for msg in _gemini_chat.history:
+        # Strip stale file refreshes and truncate old tool outputs ONCE before
+        # entering the tool loop (not per-round — history entries don't change).
+        if _gemini_chat and _get_gemini_history_list(_gemini_chat):
+            for msg in _get_gemini_history_list(_gemini_chat):
                 if msg.role == "user" and hasattr(msg, "parts"):
                     for p in msg.parts:
                         if hasattr(p, "function_response") and p.function_response and hasattr(p.function_response, "response"):
@@ -528,6 +579,7 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                                         val = val[:_history_trunc_limit] + "\n\n... [TRUNCATED BY SYSTEM TO SAVE TOKENS.]"
                                     r["output"] = val
 
+        for r_idx in range(MAX_TOOL_ROUNDS + 2):
             resp = _gemini_chat.send_message(payload)
             txt = "\n".join(p.text for c in resp.candidates if getattr(c, "content", None) for p in c.content.parts if hasattr(p, "text") and p.text)
             if txt: all_text.append(txt)
@@ -543,13 +595,15 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
             
             # Guard: if Gemini reports input tokens approaching the limit, drop oldest history pairs
             total_in = usage.get("input_tokens", 0)
-            if total_in > _GEMINI_MAX_INPUT_TOKENS and _gemini_chat and _gemini_chat.history:
-                hist = _gemini_chat.history
+            if total_in > _GEMINI_MAX_INPUT_TOKENS and _gemini_chat and _get_gemini_history_list(_gemini_chat):
+                hist = _get_gemini_history_list(_gemini_chat)
                 dropped = 0
                 # Drop oldest pairs (user+model) but keep at least the last 2 entries
                 while len(hist) > 4 and total_in > _GEMINI_MAX_INPUT_TOKENS * 0.7:
-                    # Rough estimate: each dropped message saves ~(chars/4) tokens
+                    # Drop in pairs (user + model) to maintain alternating roles required by Gemini
                     saved = 0
+                    for _ in range(2):
+                        if not hist: break
                         for p in hist[0].parts:
                             if hasattr(p, "text") and p.text:
                                 saved += len(p.text) // 4
@@ -558,8 +612,8 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                                 if isinstance(r, dict):
                                     saved += len(str(r.get("output", ""))) // 4
                         hist.pop(0)
-                    total_in -= max(saved, 100)
                         dropped += 1
+                    total_in -= max(saved, 200)
                 if dropped > 0:
                     _append_comms("OUT", "request", {"message": f"[GEMINI HISTORY TRIMMED: dropped {dropped} old entries to stay within token budget]"})
 
@@ -579,8 +633,8 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
 
                 if i == len(calls) - 1:
                     if file_items:
-                        file_items = _reread_file_items(file_items)
-                        ctx = _build_file_context_text(file_items)
+                        file_items, changed = _reread_file_items(file_items)
+                        ctx = _build_file_context_text(changed)
                         if ctx:
                             out += f"\n\n[SYSTEM: FILES UPDATED]\n\n{ctx}"
                     if r_idx == MAX_TOOL_ROUNDS: out += "\n\n[SYSTEM: MAX ROUNDS. PROVIDE FINAL ANSWER.]"
@@ -616,7 +670,15 @@ _FILE_REFRESH_MARKER = "[FILES UPDATED"
 
 
 def _estimate_message_tokens(msg: dict) -> int:
-    """Rough token estimate for a single Anthropic message dict."""
+    """
+    Rough token estimate for a single Anthropic message dict.
+    Caches the result on the dict as '_est_tokens' so repeated calls
+    (e.g., from _trim_anthropic_history) don't re-scan unchanged messages.
+    Call _invalidate_token_estimate() when a message's content is modified.
+    """
+    cached = msg.get("_est_tokens")
+    if cached is not None:
+        return cached
     total_chars = 0
     content = msg.get("content", "")
     if isinstance(content, str):
@@ -634,7 +696,14 @@ def _estimate_message_tokens(msg: dict) -> int:
                     total_chars += len(_json.dumps(inp, ensure_ascii=False))
             elif isinstance(block, str):
                 total_chars += len(block)
-    return max(1, int(total_chars / _CHARS_PER_TOKEN))
+    est = max(1, int(total_chars / _CHARS_PER_TOKEN))
+    msg["_est_tokens"] = est
+    return est
+
+
+def _invalidate_token_estimate(msg: dict):
+    """Remove the cached token estimate so the next call recalculates."""
+    msg.pop("_est_tokens", None)
 
 
 def _estimate_prompt_tokens(system_blocks: list[dict], history: list[dict]) -> int:
@@ -646,7 +715,7 @@ def _estimate_prompt_tokens(system_blocks: list[dict], history: list[dict]) -> i
         total += max(1, int(len(text) / _CHARS_PER_TOKEN))
     # Tool definitions (rough fixed estimate — they're ~2k tokens for our set)
     total += 2500
-    # History messages
+    # History messages (uses cached estimates for unchanged messages)
     for msg in history:
         total += _estimate_message_tokens(msg)
     return total
@@ -681,6 +750,7 @@ def _strip_stale_file_refreshes(history: list[dict]):
             cleaned.append(block)
         if len(cleaned) < len(content):
             msg["content"] = cleaned
+            _invalidate_token_estimate(msg)
 
 
 def _trim_anthropic_history(system_blocks: list[dict], history: list[dict]):
@@ -772,6 +842,28 @@ def _strip_cache_controls(history: list[dict]):
                 if isinstance(block, dict):
                     block.pop("cache_control", None)
 
+def _add_history_cache_breakpoint(history: list[dict]):
+    """
+    Place cache_control:ephemeral on the last content block of the
+    second-to-last user message. This uses one of the 4 allowed Anthropic
+    cache breakpoints to cache the conversation prefix so the full history
+    isn't reprocessed on every request.
+    """
+    user_indices = [i for i, m in enumerate(history) if m.get("role") == "user"]
+    if len(user_indices) < 2:
+        return  # Only one user message (the current turn) — nothing stable to cache
+    target_idx = user_indices[-2]
+    content = history[target_idx].get("content")
+    if isinstance(content, list) and content:
+        last_block = content[-1]
+        if isinstance(last_block, dict):
+            last_block["cache_control"] = {"type": "ephemeral"}
+    elif isinstance(content, str):
+        history[target_idx]["content"] = [
+            {"type": "text", "text": content, "cache_control": {"type": "ephemeral"}}
+        ]
+
+
 def _repair_anthropic_history(history: list[dict]):
     """
     If history ends with an assistant message that contains tool_use blocks
@@ -809,23 +901,36 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
         _ensure_anthropic_client()
         mcp_client.configure(file_items or [], [base_dir])
 
-        system_text = _get_combined_system_prompt() + f"\n\n<context>\n{md_content}\n</context>"
-        system_blocks = _build_chunked_context_blocks(system_text)
+        # Split system into two cache breakpoints:
+        # 1. Stable system prompt (never changes — always a cache hit)
+        # 2. Dynamic file context (invalidated only when files change)
+        stable_prompt = _get_combined_system_prompt()
+        stable_blocks = [{"type": "text", "text": stable_prompt, "cache_control": {"type": "ephemeral"}}]
+        context_text = f"\n\n<context>\n{md_content}\n</context>"
+        context_blocks = _build_chunked_context_blocks(context_text)
+        system_blocks = stable_blocks + context_blocks
 
         user_content = [{"type": "text", "text": user_message}]
 
         # COMPRESS HISTORY: Truncate massive tool outputs from previous turns
         for msg in _anthropic_history:
             if msg.get("role") == "user" and isinstance(msg.get("content"), list):
+                modified = False
                 for block in msg["content"]:
                     if isinstance(block, dict) and block.get("type") == "tool_result":
                         t_content = block.get("content", "")
                         if _history_trunc_limit > 0 and isinstance(t_content, str) and len(t_content) > _history_trunc_limit:
                             block["content"] = t_content[:_history_trunc_limit] + "\n\n... [TRUNCATED BY SYSTEM TO SAVE TOKENS. Original output was too large.]"
+                            modified = True
+                if modified:
+                    _invalidate_token_estimate(msg)
 
         _strip_cache_controls(_anthropic_history)
         _repair_anthropic_history(_anthropic_history)
         _anthropic_history.append({"role": "user", "content": user_content})
+        # Use the 4th cache breakpoint to cache the conversation history prefix.
+        # This is placed on the second-to-last user message (the last stable one).
+        _add_history_cache_breakpoint(_anthropic_history)
 
         n_chunks = len(system_blocks)
         _append_comms("OUT", "request", {
@@ -850,13 +955,16 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
                     ),
                 })
 
+            def _strip_private_keys(history):
+                return [{k: v for k, v in m.items() if not k.startswith("_")} for m in history]
+
             response = _anthropic_client.messages.create(
                 model=_model,
                 max_tokens=_max_tokens,
                 temperature=_temperature,
                 system=system_blocks,
                 tools=_get_anthropic_tools(),
-                messages=_anthropic_history,
+                messages=_strip_private_keys(_anthropic_history),
             )
 
             # Convert SDK content block objects to plain dicts before storing in history
@@ -939,10 +1047,10 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
                         "content":     output,
                     })
 
-            # Refresh file context after tool calls and inject into tool result message
+            # Refresh file context after tool calls — only inject CHANGED files
             if file_items:
-                file_items = _reread_file_items(file_items)
-                refreshed_ctx = _build_file_context_text(file_items)
+                file_items, changed = _reread_file_items(file_items)
+                refreshed_ctx = _build_file_context_text(changed)
                 if refreshed_ctx:
                     tool_results.append({
                         "type": "text",

config.toml

@@ -10,11 +10,11 @@ system_prompt = "DO NOT EVER make a shell script unless told to. DO NOT EVER mak
 palette = "10x Dark"
 font_path = "C:/Users/Ed/AppData/Local/uv/cache/archive-v0/WSthkYsQ82b_ywV6DkiaJ/pygame_gui/data/FiraCode-Regular.ttf"
 font_size = 18.0
-scale = 1.1
+scale = 1.25
 
 [projects]
 paths = [
     "manual_slop.toml",
     "C:/projects/forth/bootslop/bootslop.toml",
 ]
-active = "C:/projects/forth/bootslop/bootslop.toml"
+active = "manual_slop.toml"

docs/Readme.md

@@ -29,7 +29,7 @@ Controls what is explicitly fed into the context compiler.
 
 - **Base Dir:** Defines the root for path resolution and tool constraints.
 - **Paths:** Explicit files or wildcard globs (e.g., src/**/*.rs). 
-- When generating a request, these files are summarized symbolically (summarize.py) to conserve tokens, unless the AI explicitly decides to read their full contents via its internal tools.
+- When generating a request, full file contents are inlined into the context by default (`summary_only=False`). The AI can also call `get_file_summary` via its MCP tools to get a compact structural view of any file on demand.
 
 ## Interaction Panels
 
@@ -46,8 +46,9 @@ Switch between API backends (Gemini, Anthropic) on the fly. Clicking "Fetch Mode
 
 ### Global Text Viewer & Script Outputs
 
-- **Last Script Output:** Whenever the AI executes a background script, this window pops up, flashing blue. It contains both the executed script and the stdout/stderr.
+- **Last Script Output:** Whenever the AI executes a background script, this window pops up, flashing blue. It contains both the executed script and the stdout/stderr. The `[+ Maximize]` buttons read directly from stored instance variables (`_last_script`, `_last_output`) rather than DPG widget tags, so they work correctly regardless of word-wrap state.
 - **Text Viewer:** A large, resizable global popup invoked anytime you click a [+] or [+ Maximize] button in the UI. Used for deep-reading long logs, discussion entries, or script bodies.
+- **Confirm Dialog:** The `[+ Maximize]` button in the script approval modal passes the script text directly as `user_data` at button-creation time, so it remains safe to click even after the dialog has been dismissed.
 
 ## System Prompts
 

docs/guide_architecture.md

@@ -1,4 +1,4 @@
-# Guide: Architecture
+# Guide: Architecture
 
 Overview of the package design, state management, and code-path layout.
 
@@ -33,10 +33,9 @@ This occurs inside aggregate.run.
 If using the default workflow, aggregate.py hashes through the following process:
 
 1. **Glob Resolution:** Iterates through config["files"]["paths"] and unpacks any wildcards (e.g., src/**/*.rs) against the designated base_dir.
-2. **Summarization Pass:** Instead of concatenating raw file bodies (which would quickly overwhelm the ~200k token limit over multiple rounds), the files are passed to summarize.py.
-3. **AST Parsing:** summarize.py runs a heuristic pass. For Python files, it uses the standard ast module to read structural nodes (Classes, Methods, Imports, Constants). It outputs a compact Markdown table.
-4. **Markdown Generation:** The final <project>_00N.md string is constructed, comprising the truncated AST summaries, the user's current project system prompt, and the active discussion branch. 
-5. The Markdown file is persisted to disk (./md_gen/ by default) for auditing.
+2. **File Item Build:** `build_file_items()` reads each resolved file once, storing path, content, and `mtime`. This list is returned alongside the markdown so `ai_client.py` can use it for dynamic context refresh after tool calls without re-reading from disk.
+3. **Markdown Generation:** `build_markdown_from_items()` assembles the final `<project>_00N.md` string. By default (`summary_only=False`) it inlines full file contents. If `summary_only=True`, it delegates to `summarize.build_summary_markdown()` which uses AST-based heuristics to produce compact structural summaries instead.
+4. The Markdown file is persisted to disk (`./md_gen/` by default) for auditing. `run()` returns a 3-tuple `(markdown_str, output_path, file_items)`.
 
 ### AI Communication & The Tool Loop
 
@@ -85,3 +84,4 @@ All I/O bound session data is recorded sequentially. session_logger.py hooks int
 - logs/comms_<ts>.log: A JSON-L structured timeline of every raw payload sent/received.
 - logs/toolcalls_<ts>.log: A sequential markdown record detailing every AI tool invocation and its exact stdout result.
 - scripts/generated/: Every .ps1 script approved and executed by the shell runner is physically written to disk for version control transparency.
+

docs/guide_tools.md

@@ -12,17 +12,22 @@ Implemented in mcp_client.py. These tools allow the AI to selectively expand its
 
 ### Security & Scope
 
-Every filesystem MCP tool passes its arguments through _resolve_and_check. This function ensures that the requested path falls under one of the allowed directories defined in the GUI's Base Dir configurations. 
+Every **filesystem** MCP tool passes its arguments through `_resolve_and_check`. This function ensures that the requested path falls under one of the allowed directories defined in the GUI's Base Dir configurations.
 If the AI attempts to read or search a path outside the project bounds, the tool safely catches the constraint violation and returns ACCESS DENIED.
 
+The two **web tools** (`web_search`, `fetch_url`) bypass this check entirely — they have no filesystem access and are unrestricted.
+
 ### Supplied Tools:
 
-* read_file(path): Returns the raw UTF-8 text of a file.
-* list_directory(path): Returns a formatted table of a directory's contents, showing file vs dir and byte sizes.
-* search_files(path, pattern): Executes an absolute glob search (e.g., **/*.py) to find specific files.
-* get_file_summary(path): Invokes the local summarize.py heuristic parser to get the AST structure of a file without reading the whole body.
-* web_search(query): Queries DuckDuckGo's raw HTML endpoint and returns the top 5 results (Titles, URLs, Snippets) using a native HTMLParser to avoid heavy dependencies.
-* fetch_url(url): Downloads a target webpage and strips out all scripts, styling, and structural HTML, returning only the raw prose content (clamped to 40,000 characters).
+**Filesystem tools** (access-controlled via `_resolve_and_check`):
+* `read_file(path)`: Returns the raw UTF-8 text of a file.
+* `list_directory(path)`: Returns a formatted table of a directory's contents, showing file vs dir and byte sizes.
+* `search_files(path, pattern)`: Executes a glob search (e.g., `**/*.py`) within an allowed directory.
+* `get_file_summary(path)`: Invokes the local `summarize.py` heuristic parser to get the AST structure of a file without reading the whole body.
+
+**Web tools** (unrestricted — no filesystem access):
+* `web_search(query)`: Queries DuckDuckGo's raw HTML endpoint and returns the top 5 results (title, URL, snippet) using a native `_DDGParser` (HTMLParser subclass) to avoid heavy dependencies.
+* `fetch_url(url)`: Downloads a target webpage and strips out all scripts, styling, and structural HTML via `_TextExtractor`, returning only the raw prose content (clamped to 40,000 characters). Automatically resolves DuckDuckGo redirect links.
 
 ## 2. Destructive Execution (run_powershell)
 

gui.py

@@ -1,4 +1,4 @@
-# gui.py
+# gui.py
 """
 Note(Gemini):
 The main DearPyGui interface orchestrator.
@@ -302,8 +302,8 @@ class ConfirmDialog:
                     dpg.add_text("Script:")
                     dpg.add_button(
                         label="[+ Maximize]",
-                        user_data=f"{self._tag}_script",
-                        callback=lambda s, a, u: _show_text_viewer("Confirm Script", dpg.get_value(u))
+                        user_data=self._script,
+                        callback=lambda s, a, u: _show_text_viewer("Confirm Script", u)
                     )
                 dpg.add_input_text(
                     tag=f"{self._tag}_script",
@@ -432,6 +432,8 @@ class App:
         self._pending_dialog_lock = threading.Lock()
 
         self._tool_log: list[tuple[str, str]] = []
+        self._last_script: str = ""
+        self._last_output: str = ""
 
         # Comms log entries queued from background thread for main-thread rendering
         self._pending_comms: list[dict] = []
@@ -748,6 +750,8 @@ class App:
         return output
 
     def _append_tool_log(self, script: str, result: str):
+        self._last_script = script
+        self._last_output = result
         self._tool_log.append((script, result))
         self._rebuild_tool_log()
         
@@ -1917,8 +1921,7 @@ class App:
                 dpg.add_text("Script:")
                 dpg.add_button(
                     label="[+ Maximize]",
-                    user_data="last_script_text",
-                    callback=lambda s, a, u: _show_text_viewer("Last Script", dpg.get_value(u))
+                    callback=lambda s, a, u: _show_text_viewer("Last Script", self._last_script),
                 )
             dpg.add_input_text(
                 tag="last_script_text",
@@ -1934,8 +1937,7 @@ class App:
                 dpg.add_text("Output:")
                 dpg.add_button(
                     label="[+ Maximize]",
-                    user_data="last_script_output",
-                    callback=lambda s, a, u: _show_text_viewer("Last Output", dpg.get_value(u))
+                    callback=lambda s, a, u: _show_text_viewer("Last Output", self._last_output),
                 )
             dpg.add_input_text(
                 tag="last_script_output",
@@ -2120,3 +2122,7 @@ def main():
 
 if __name__ == "__main__":
     main()
+
+
+
+