Agents¶

LLM-backed entities that run the incident pipeline. Each agent has a trust level, a role set, an LLM provider/model binding, and a system prompt.

List¶

Route: /agents Role gating: read for all; create / edit / delete require admin.

Card grid with name, enabled toggle, LLM provider/model, trust level, assigned roles, and a token-usage progress bar against the configured budget.

Create¶

Modal collects:

Name and description.
LLM provider (openai / deepseek / anthropic / kimi / llamacpp / vllm) and model.
Trust level — autonomous, supervised, manual. Determines the approval gate; see below.
Role checkboxes — which pipeline stages this agent can handle: triage, diagnose, validate, execute, review.
Patrol interval (minutes).
Monthly token budget.

Detail¶

Route: /agents/{id} Role gating: admin.

Configuration panel with the following sections.

Identity¶

Name, description.

LLM¶

Provider, model, Refresh Models button (pulls the live model list from the provider), temperature, max tokens, reasoning toggle for reasoning-capable models.

Pipeline¶

Trust level, role checkboxes, patrol interval, token budget.

System prompt¶

Free-form custom prompt prepended to every stage. If set, this overrides the default Jinja templates for this agent.

Skills¶

Markdown knowledge modules currently assigned to the agent. Remove button per row plus a dropdown to add more.

Stats (read-only)¶

Incidents resolved.
Currently active incidents.
Tokens used this period.
Budget remaining.

Trust gate¶

Trust level interacts with each recipe's risk level via the should_request_approval server-side gate.

Trust × risk	`low`	`medium`	`high`
`autonomous`	auto	approval	approval
`supervised`	approval	approval	approval
`manual`	approval	approval	approval

The LLM cannot self-approve. Risk classification on a recipe is the operator's responsibility, not the agent's.

skills.md — assignable knowledge modules
incidents.md — agents are assigned to incidents
settings.md — global LLM provider configuration and prompt templates