Profiles

Profiles define the agent's identity, tools, and behaviour for a specific domain.

Profile definition (`navi/profiles/base.py`)

Each profile is loaded from a directory under navi/profiles/<id>/:

config.json — all fields below
system_prompt.txt — domain-specific instructions
subagent_system_prompt.txt — injected into subagents spawned from this profile (optional)

@dataclass
class AgentProfile:
    id: str                        # unique identifier
    name: str
    description: str
    system_prompt: str             # loaded from system_prompt.txt
    enabled_tools: list[str]       # tools available in the main loop
    llm_backend: str = "ollama"
    model: str = "gemma4:31b-cloud"
    max_iterations: int = 10
    temperature: float = 0.7
    planning_enabled: bool = False
    short_description: str = ""    # 1-line summary shown to all profiles
    full_description: dict = {}    # keys: specialization, when_to_use, key_tools

    # Thinking mechanics (see docs/agent.md for details)
    think_enabled: bool = True
    iteration_budget_enabled: bool = True
    planning_reflect_enabled: bool = False
    goal_anchoring_enabled: bool = True
    goal_anchoring_interval: int = 5
    anti_stall_enabled: bool = True
    anti_stall_threshold: int = 8
    step_validation_enabled: bool = False
    adaptive_replan_enabled: bool = False

    # Sub-agent configuration
    subagent_tools: list[str] = []
    subagent_planning_enabled: bool = False
    subagent_system_prompt: str = ""  # loaded from subagent_system_prompt.txt

Active profiles

ID	Name	Model	Temp	Planning
`secretary`	Personal Secretary	gemma4:31b-cloud	0.7	Yes
`server_admin`	Server Administrator	gemma4:31b-cloud	0.2	Yes
`developer`	Tool Developer	gemma4:31b-cloud	0.2	Yes

All profiles share a base tool set. User tools from tools/enabled.json are merged in at runtime.

System prompt construction

The LLM sees (injected fresh on every call, never stored in session):

{persona.txt content}

---

{profile system_prompt.txt content}

persona.txt — global layer: personality, CONTEXT FIRST principle, self-extension rules, scratchpad/todo/memory instructions, delegation rules.

system_prompt.txt — domain layer: tool priorities, workflow, safety rules for this profile.

Adding a profile

Create directory navi/profiles/my_profile/

Add config.json:

{
"id": "my_profile",
"name": "My Profile",
"description": "...",
"short_description": "...",
"model": "gemma4:31b-cloud",
"temperature": 0.5,
"max_iterations": 30,
"planning_enabled": true,
"think_enabled": true,
"iteration_budget_enabled": true,
"planning_reflect_enabled": false,
"goal_anchoring_enabled": true,
"goal_anchoring_interval": 5,
"anti_stall_enabled": true,
"anti_stall_threshold": 8,
"step_validation_enabled": false,
"adaptive_replan_enabled": false,
"subagent_planning_enabled": false,
"subagent_tools": ["todo", "filesystem", "terminal"],
"enabled_tools": ["todo", "scratchpad", "web_search", "filesystem"]
}

Add system_prompt.txt with domain-specific instructions.
Optionally add subagent_system_prompt.txt.
The profile is auto-discovered at startup — no registration needed.

Profile switching

switch_profile tool updates session.profile_id in the DB. After each tool execution batch, run_stream() checks for a profile change and reloads profile + tools. Takes effect on the next LLM call.