Add context providers: dynamic system message injection per LLM call ...

- navi/context_providers/ registry + built-in public_url provider (global, always injected)
- context_providers/ user directory, hot-reloaded via reload_tools
- AgentProfile.context_providers field for per-profile opt-in providers
- Agent._collect_context_injections() called before every tool-calling loop
- reload_tools now reloads both user tools and user context providers
- manuals/write_context_provider.md for Navi, docs/context_providers.md reference

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Set temperature=1.0, top_k=64, top_p=0.95 for all profiles (Google recommended for gemma4) ...

Also fixes discuss profile memory tools: use combined "memory" tool name, not nonexistent split variants.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Add per-phase planning flags and planning_mandatory ...

- planning_mandatory: disables DIRECT shortcut, forces all phases to run
- planning_phase1_enabled / phase2_enabled / phase3_enabled: per-phase toggles
- planning_phase2_enabled replaces planning_reflect_enabled (migrated in loader with backward compat)
- Migrate all profile configs; rewrite docs/profiles.md as full config reference

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Add Ollama multi-server fallback with in-memory blacklisting ...

- New FallbackOllamaBackend (navi/llm/fallback.py): tries servers and
  models in priority order; on LLMConnectionError blacklists the server
  for the process lifetime, on LLMModelNotFoundError blacklists the
  (server, model) pair — eliminates latency from repeated failed probes
- OllamaBackend now raises typed LLMConnectionError / LLMModelNotFoundError
  instead of bare LLMBackendError; accepts list[str] | str | None for model
- AgentProfile.model changed from str to list[str] (str auto-normalised);
  all profiles updated to ["gemma4:31b-cloud", "gemma4:26b-a4b-it-q4_K_M"]
- New config field OLLAMA_BACKENDS_FILE: path to [{host, api_key?}] JSON;
  when set, registry creates FallbackOllamaBackend instead of OllamaBackend
- ollama_backends.json template added (gitignored — contains API key)
- current_model ContextVar type widened to list[str] | str | None

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Use gemma4 cloud model by default

Improve subagent system: isolated tools, custom prompts, context transfer, timeout ...

AgentProfile:
- New fields: subagent_tools, subagent_planning_enabled, subagent_system_prompt
- loader.py: loads subagent_tools/subagent_planning_enabled from config.json,
  reads optional subagent_system_prompt.txt per profile

Profiles:
- Each profile now has a dedicated subagent_tools list (focused subset, no admin tools)
- subagent_planning_enabled: false (configurable per profile)
- New subagent_system_prompt.txt per profile with executor-focused instructions

run_ephemeral:
- Uses profile.subagent_tools instead of enabled_tools
- Builds subagent context without persona or profiles block (focused executor)
- Injects subagent_system_prompt after profile.system_prompt
- Accepts context_transfer: priming exchange injected before task message
- Wall-clock timeout (default 5 min) checked per iteration
- Returns (result_text, completed: bool) instead of bare string
- Optionally runs planning phase if profile.subagent_planning_enabled

spawn_agent:
- Removed briefing param; task is now fully self-contained
- Added system_prompt param: custom injected prompt for this specific task
- Auto-reads parent scratchpad context_transfer section via get_section()
- Result prefixed with [STATUS: completed|limit_reached]
- Timeout 300s

scratchpad:
- Added get_section(session_id, section) helper for cross-session reads

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Add profile discoverability: list_profiles tool + system prompt injection ...

- AgentProfile: new short_description (1-line) and full_description (dict
  with specialization / when_to_use / key_tools) fields
- All 3 profile configs: structured descriptions added; list_profiles added
  to enabled_tools
- _build_system_prompt: now accepts full AgentProfile; injects compact
  "Available profiles" block into every system prompt so Navi always knows
  what other profiles exist and when to switch — dynamically, no hardcoding
- ListProfilesTool: new built-in; returns structured per-profile details
  (specialization, when_to_use, key_tools); accepts optional profile_id
  for single-profile lookup
- registry: register list_profiles_tool after profiles registry is built

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Restructure profiles: directory-based format with config.json + system_prompt.txt ...

Each profile is now a subdirectory under navi/profiles/ containing:
  config.json       — model, temperature, enabled_tools, and other settings
  system_prompt.txt — raw system prompt, editable without touching Python

Added navi/profiles/loader.py for auto-discovery of profile directories.
Removed individual profile .py files (secretary, server_admin, smart_home, developer).
profiles/__init__.py now simply calls load_profiles_from_dir() at import time.

New profiles can be added by creating a directory with the two required files —
no Python changes needed.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>