sessions: a pasted image lands in the session directory, and the notice says where ...

An image pasted into the chat lived only in the transcript. The system prompt of
every session names `session_files/<id>/` as the place its files live, so an agent
looking for "the attached images" went there, found nothing, and spent turns on
fruitless `find` calls before giving up.

Now the agent's non-hidden turn writes each pasted image into that directory as
`image_N.<ext>` — the extension sniffed from the bytes, the bytes stored as they
arrived, so a PNG keeps its alpha channel. Numbering runs across the session, and
a picture sent twice reuses the file already holding it.

The paths go into the hidden context copy of the message: images past the context
budget are not sent to the model at all, so the notice names them for `image_view`
instead. The line is written by the agent rather than the websocket handler, which
is the layer that knows the names the files actually took — including for a message
queued behind a running turn.

A save that fails is logged and skipped: it never costs the turn.

subagents, secrets: an honest result contract, and two leaks closed ...

A pass over the sub-agent system, plus the two findings from the previous one.

Leaks:

- `redact_args` / `is_sensitive_key` (navi/tools/_internal/redact.py) mask
  credential-shaped keys at every log site that prints tool arguments — by key
  name, for all tools, so a future MCP tool is covered without declaring
  anything. ssh_exec passwords were sitting in the prod journal in plaintext.
- `mcp_servers.d/*.json` are tracked in git and carried the scaffolding
  machine's absolute paths, so navi-3d/navi-web silently vanished from the
  toolset off that machine. They now hold project-relative paths, resolved in
  `McpClient.open_transport` — not at load time, because create_mcp_server
  round-trips every config file through save_mcp_servers.

Sub-agent result contract:

- `run_ephemeral` returns a `SubAgentOutcome` (text + status: ok, timeout,
  max_iterations, thinking_stall, user_stop, context_overflow) instead of
  `(text, bool)`. Every exit routes through `SubAgentRunner._finish`, so token
  accounting is never dropped and a partial run always carries a progress
  report — the stop-after-stream path used to return a bare string.
- `spawn_agent` renders its header from the status. Before this, every short
  run reached the parent as "hit iteration limit", and the parent repeats that
  diagnosis to the user — a timeout was reported as an iteration limit.
- `ContextTooLargeError` no longer kills a sub-agent: the parent compresses its
  own context, a sub-agent has no session to compress into, so it stops with
  `context_overflow` and hands back what it did rather than surfacing as
  "Sub-agent failed: …" with the whole run discarded.
- The result is capped at 8000 chars (head and tail kept) so a long run cannot
  flood the parent's context, and tool arguments in the progress report go
  through `redact_args`.
- The navi-3d calling convention left the runner for the server's own tool
  schemas — a generic runner should not know one MCP server's path shapes.
- Validation moved inside spawn_agent's try: a bad argument is a clean
  ToolResult the model can read, not an exception in the parent's loop.

Tests: 1636 passed, 1 skipped. New: SubAgentOutcome paths and headers, result
truncation, context overflow, clean argument failures.

agent: a profile switch now survives the turn that made it ...

switch_profile repoints the session with one narrow UPDATE, and the run's own
save() — which lands right after every tool batch, the switch's own batch
included — wrote its stale in-memory profile back over it. The post-turn
reload then read the row it had just clobbered, saw no change, and left the
turn bound to the old profile's tools: the agent called exactly the tools
switch_profile had just advertised ("Newly available: ssh_exec, terminal, …")
and got "tool not found" for every one of them. Prod shows both halves — the
session that reported two switches kept the profile it started with, and
agent.profile_reloaded appears zero times in the whole boot.

The reload now compares against the profile the run is bound to
(bound_profile_id), which set_profile cannot move, instead of against
session.profile_id, which the store either rewrites or mutates to the new
value — making the old guard false in both branches by construction. And
save() leaves the profile_id column alone on conflict: set_profile owns it
after creation, the same way name/created_at are owned elsewhere.

A tool the live tool_map does not hold is now logged (tool.not_found, with
profile and live tool count). It previously left no trace at all in the
journal, which is why this took a database dig to find.

Three tests, each verified to fail without its fix: the next LLM call is
offered the new profile's tools, save() does not rewrite profile_id, and a
missing tool is logged.

planning: replace the mandatory pre-turn gate with an agent-invoked plan tool ...

- Phase 2 (critique) retired; observe/MODE and the top-level DIRECT shortcut
  removed (sub-agents keep DIRECT for trivial subtasks)
- replan merged into plan: `reason` (+ updated_goal) packs the re-plan
  context, without a reason it is fresh planning
- both phases call the LLM with think=False — cloud reasoning models leak
  their chain-of-thought into structured output on non-streaming calls —
  and strip the gemma "thought<channel|>" content artifact
- Phase 1 conversation windowed to ~20k chars, newest-first with the
  original task pinned (28.7k-token prompts came back as 1-token output)
- confirmation by COMPLEXITY: the tool result tells the agent to present
  complex plans and wait; sub-agents keep the execute-now injection
- PlanningStatus/PlanReady reach the UI mid-turn via current_event_sink
  (ctx.event_sink is None in the agent loop — events silently never
  reached the WS before)
- agent gate, casual-message detector and adaptive re-plan nudges removed;
  anti_stall keeps only stall detection

Автономность мелких моделей: OUTPUT DISCIPLINE, milestone-todo, перехват финала хода ...

Два последовательных захода над одной проблемой — мелкие модели (12–30B) в navi_code
теряют автономность на трудных шагах: «остановился поболтать» вместо действия и
слишком большое расстояние между пунктами плана.

Заход 1 (З1–З3):
- З1: OUTPUT DISCIPLINE в системном промпте navi_code — «act, don't announce»,
  без few-shot антипримеров. Контракт хода: ответ без tool_calls = конец хода, поэтому
  объявление намерения текстом убивает автономность; правила заставляют вызывать
  инструмент в том же ходе.
- З2: плоский todo + метка группы milestone + декомпозиция. _parse_plan_steps
  возвращает list[tuple[milestone, text]]; milestone — метка группировки (не сущность,
  без статуса), «done» вычисляется при рендеринге; подшаги = больше плоских шагов
  (без вложенности). TUI side-panel группирует по milestone (плоский фолбэк при пустом
  milestone). Plan depth: max 15→20 + правило декомпозиции.
- З3: adaptive re-plan «длинный шаг» — nudge «разбей шаг» при in_progress ≥ порога
  итераций без смены todo (порог 4, раньше общего anti-stall warning на 8).

Заход 2 (шаги 1–3, после cloud-теста 31b vs 12b):
Корневая структурная причина: весь спасательный механизм (anti-stall warning с явным
предложением reflect, adaptive re-plan) живёт только внутри tool-цикла — nudge
инжектируется в pre_turn *следующей* итерации, которой при «остановился поболтать»
нет (ход закрылся по return до post_turn). 31b застревала через «продолжаю
tool-итерации» → дожала до warning → спаслась; 12b — через «замолчала текстом» → мимо
всех nudge.

- Шаг 1: перехват финала хода. Если модель выдала bare-text, но в todo есть открытые
  шаги (pending/in_progress) и лимит не исчерпан — НЕ эмитить StreamEnd, а сохранить
  ассистентский текст в session.context, поставить системный nudge и continue
  (без StreamEnd, без workers — консистентно с multi-iteration tool-турами). Счётчик
  final_interceptions на AgentTurnContext, лимит final_intercept_limit (default 2),
  эскалация жёсткости (мягкий → «second stop»). has_open_steps в todo.py: пустой
  todo → False (защита casual-сообщений), failed/skipped терминальны. Профильные
  флаги final_intercept_enabled/limit в base.py + loader + admin.
- Шаг 2: жёсткий reflect-триггер в промпте — «~3 tool attempts on the same step
  without progress → call reflect IN THIS TURN (tool call, not reasoning aloud)».
- Шаг 3: открыть replan для застревания — «call replan when reflect showed the whole
  approach is dead (not one failed step, but the approach itself)».

Тесты: 874 passed, 1 skipped. Новые — has_open_steps (5), final intercept (5),
milestone-группировка, adaptive long-step nudge, парсер шагов с milestone-маркером.

cloud: navi_code model → gemma4:31b-cloud для тестирования догадки (31b признала
застревание, 12b — нет); .env cloud-host уже gitignored.

Co-Authored-By: Claude <noreply@anthropic.com>

compressor: split in-flight turn in midturn mode + flush incrementally ...

Two related fixes for long autonomous turns in planning profiles (navi_code):

A1 — partition_messages turn-based branch held the in-flight (current) turn
verbatim when turns > keep_recent, so midturn compression was shallow
(e.g. 150 -> 141 messages). Now, when keep_recent_messages is set, the
in-flight turn is split like partition_current_turn_messages: head (user
request) + tail (recent tool steps) kept, middle summarized. The adaptive
swap is disabled in midturn mode (it could move the in-flight turn into
old_turns and summarize the current request whole). First branch
(len(turns) <= keep_recent) is untouched, so locked-in midturn tests hold.

B1 — agent.run_stream had no try/finally around the for-loop, so an
asyncio.CancelledError (server restart/shutdown) unwound the stack with no
flush: all in-memory turn messages (sequence_number < 0) were lost, only the
user message survived. Add incremental save() after planning, after the
assistant tool-call decision, and after each tool result, so a crash loses at
most the single in-flight tool call, not the whole turn. B2 (try/except
safety-net) was dropped: B1 leaves no window where an append is unsaved.

Tests: midturn split with many turns (partition + compress_session), and
crash/cancel persistence via a snapshot session store that mirrors the DB
boundary.

Co-Authored-By: Claude <noreply@anthropic.com>

compression: fix auto-compress no-op on few-huge-messages + honest status ...

Root cause: the compression gate (should_compress) measures tokens, but the
partition measures message/turn count, and CompressionStarted was emitted
before the attempt. For navi_code's "few very large messages" shape (one big
file read = 1 user + assistant + 1 huge tool result, 66k tokens in 3 messages)
the gate fired, the UI showed "compression", but partition returned
to_summarize=[] -> compress_context None -> nothing shrank. The agent kept
going until the window overflowed. It wasn't running "during" compression —
there was no compression, just a no-op the user mistook for one.

A. Per-message head/tail truncation in context_builder.build(): oversized
   tool/assistant messages (over context_message_token_budget, 0=num_ctx//6)
   are capped head+marker+tail in the LLM view only (model_copy — stored
   history and reloads are never affected). A single huge tool result can no
   longer alone blow the window; user/system messages are never truncated.

B. Token-budget hard-truncate fallback in compress_session: when partition
   no-ops but tokens exceed the threshold, drop oldest turns to num_ctx*0.5.
   _hard_truncate is now token-aware (was a fixed message-count floor that
   no-oped on <=6 messages even when huge). New would_compress() predicts
   compress_session's real outcome with no LLM call.

C. Honest CompressionStarted: _compression_events_midturn/_preturn emit it
   only after would_compress() confirms the partition (or token-budget
   fallback) can actually shrink the stored context — no more "compression"
   status with no ContextCompressed to follow.

Bonus: post-turn CompressionWorker now passes keep_recent_messages=
max(12, context_keep_recent*2), matching the midturn path, so a single long
autonomous turn compresses post-turn too (was always a no-op).

Tests (+14): would_compress agreement, token-budget fallback, token-aware
hard_truncate, build() truncation (preserves user, no mutation, head+tail),
agent no-CompressionStarted-when-nothing-to-compress, worker single-long-turn.

Co-Authored-By: Claude <noreply@anthropic.com>

Navi Code: force context compression via typed /compact control message ...

Forced /compact previously sent a chat message, which ran a full agent turn
that only produced summary text instead of running the real context compressor.
Worse, even when wired correctly, forced compact always reported "Nothing to
compact yet — the context is still small" regardless of context size: the typical
navi_code shape is a single long autonomous turn (1 user message + many tool
iterations = one turn), and partition_messages finds nothing to summarize when
turns <= keep_recent. The midturn auto-compress path already bypassed this via
keep_recent_messages (intra-turn split), but compact_stream passed
keep_recent_messages=None, so the fallback was disabled.

Changes:
- WS protocol: {"type":"compact"} control message (distinct from {"type":
  "message"}); rejected while an agent turn is active to avoid racing the agent.
- Agent.compact_stream: forced compression that bypasses the token threshold
  but still runs the real compressor; passes keep_recent_messages=max(12,
  context_keep_recent*2) so a single long turn compresses via intra-turn split
  (mirrors midturn auto-compress). Raises NothingToCompactError when context is
  genuinely too small.
- Orchestrator.run_compact + clear_run: broadcast agent events to subscribers,
  end with done marker, surface NothingToCompactError as an error event.
- Terminal client: ws_client.send accepts str|dict; CompactCommand enqueues
  {"type":"compact"}; TUI distinguishes forced compact (no stream_start) from
  in-turn auto-compress via the _streaming flag.
- Tests: compact_stream (incl. single-long-turn regression), WS handler
  dispatch/rejection, run_compact event/error broadcasting, ws_client send,
  compact command.

Co-Authored-By: Claude <noreply@anthropic.com>

Isolate sub-agent todo + render live todo in TUI side panel ...

Phase 1 — sub-agent todo isolation (backend):
- Add current_todo_session_id ContextVar; subagent_runner scopes it to the
  sub-agent's ephemeral run id so its auto-populated plan and todo updates
  land in an isolated KV row instead of clobbering the parent session's todo
  (which the parent's goal-anchoring reads every iteration).
- todo._sid() and planning.set_tasks prefer current_todo_session_id; the
  parent run leaves it unset, so all existing todo consumers (anti-stall,
  goal anchor, get_progress_message) behave exactly as before.

Phase 2 — live todo in the TUI right column:
- TodoUpdated event + emit it from the agent loop after planning auto-populate
  and after each tool-execution turn.
- GET /sessions/{id}/todos reads the parent session's todo KV row (explicit
  user_id/session_id, optional injected kv).
- api.get_todos + TodoList/TodoPanel widgets: status-coloured markers
  (pending dim, in_progress accent+bold, done success, failed error, skipped
  dim), progress header, scrollable panel below the auto-height info block.
- Hybrid delivery: REST seeds the panel on attach/switch, todo_updated WS
  events update it live.

Sub-agent todos as nested sub-lists is deferred to a later phase.

Co-Authored-By: Claude <noreply@anthropic.com>

tui: show the currently-served model in the status panel ...

The status panel's Model line was fed the global ollama_default_model, not the
session/profile model, and the server never told the client which model
actually served a call. Now:

- Backends stamp the resolved model onto LLMChunk (first chunk) / LLMResponse.
  The fallback backend reports the model that survived its server+model
  priority list (may differ from the profile's first choice).
- New ModelInfo event ({"type":"model_info","model":...}) emitted once per
  turn from agent._consume_stream, re-emitted only when the model changes
  across iterations. Additive WS event — old clients ignore it.
- TUI: attach_session/switch fetch the profile's configured model (first of
  profile.model) via api.get_profile_model so the panel shows a value before
  the first request; model_info then refines it to the actually-served model.
  Not forwarded to the chat panel. raw CLI prints "[model] ...".

Co-Authored-By: Claude <noreply@anthropic.com>

agent: skip planning for casual greetings + strengthen DIRECT shortcut in Phase 1 ...

- Add fast _is_casual_message heuristic in navi/core/agent.py. Greetings and
  social chat (e.g. 'привет', 'как дела', 'hi', 'thanks') bypass planning even
  on the first session message, unless planning_mandatory is enabled.
- Strengthen Phase 1 planning prompt in navi/core/planning.py: explicitly
  require DIRECT output for greetings, simple questions, and one-step
  instructions.
- Fix broken ContextCompressed import in navi/core/compressor.py.
- Add unit tests covering the new heuristic and DIRECT prompt.

Co-Authored-By: Claude <noreply@anthropic.com>

Review fixes: restore _build_sessions, fix flags, search filter, tests ...

- Restored _load_messages_map and _build_sessions helpers that were
  accidentally dropped in Phase 5 (list_all/list_page/search_list
  called them but they were missing, causing NameError at runtime)
- _build_sessions now filters messages by is_display so list methods
  return consistent display-only history like get()
- count_all/search_list EXISTS subquery now filters to is_display=true
  so search only matches visible chat messages
- Updated pg_session_store docstring to remove stale dual-write claim
- compressor summary_msg now defaults to is_display=False
- Added unit tests for message flags (agent, compressor, planning)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Phase 2: Dual-write with is_context/is_display flags on Message ...

- Message model gets is_context and is_display bools
- PgSessionStore.save() writes flags directly to session_messages
- Agent sets is_context=False on display-only messages, is_display=False on context-only
- Planning: plan context msg is_display=False, plan marker is_context=False
- Compression: summarized messages get is_context=False, summary added to messages with is_display=False
- Tests updated for extra user display+context messages per turn

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Add subagent progress report on failure ...

When a subagent stops (timeout, max iterations, thinking stall, user stop),
it now returns a structured progress report built from its local message
context, so the parent agent knows what tools were called and what was
accomplished before the stop.

- Add _build_progress_report() to SubAgentRunner
- Report includes: turn number, assistant text, tool calls with results
- Prepended to result_text for every stop reason (completed also gets it)
- Updated test_run_ephemeral_complete to expect the report prefix

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Fix token counting: show only completion tokens, not cumulative prompt+completion ...

The token_count displayed next to assistant messages was summing
prompt_tokens + completion_tokens across ALL tool-calling iterations,
giving hundreds of thousands of tokens for multi-turn conversations.

Now:
- token_count (coins icon) = only completion tokens generated by the model
- context_tokens (ContextBar) = only prompt tokens (context size sent to LLM)

This gives users a realistic measure of how much the model actually generated.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Extract ContextCompressor, fix STL viewer, expand test suite, add architecture audit docs ...

- Extract ContextCompressor from agent.py (Step 1 of god-object refactor)
- Add retry + hard-truncate fallback logic to ContextCompressor
- Add unit tests: agent loop (14), compressor (18), KV store (8),
  auth encrypt (3), auth deps (13), todo/scratchpad/image_view/memory
- Fix WebGL STL viewer: allow-same-origin sandbox + graceful fallback
- Add CompressionStarted event and client-side compression notice
- Add docs/architecture_weak_spots.md and plan_01_god_object_agent.md
- Update test_events.py and test_agent_context_size.py for new logic

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>