Model Autonomic Agents library
Unattended Autonomic Agent templates that load tenant playbooks from the model skills library. Each mandate is a playbook, not a persona: Purpose, Context/fitness, Sense-Reason-Act-Evaluate, how fitness is ensured, and stop rules. Canonical data is DataPool. Default notify is in-app. See Autonomic Agents and skill_id: autonomic-agents.
These are business templates (watchers). They are not the repo-wired platform specialists (platform-bulk-reader, platform-code-specialist) that appear in the Trace subagent catalog without import.
Document information
| Field | Value |
|---|---|
| Canonical URL | /docs/07_ai-agents-and-mcp/model_agents/00_index |
| Version (published date) | 2026-08-27 |
| Tags | ai, agents, autonomic, playbooks, datapool |
How to install
In Trace AI, ask to install a named model agent. Trace loads load_platform_skill with skill_id: model-agent-import, installs missing tenant skills via model-skill-import (including Prerequisites), then create_autonomic_agent with status: draft. It does not activate or run the agent unless you ask.
| Slug | Job | Required tenant skills | Page |
|---|---|---|---|
sales-ready-lead-watcher | Act on new sales-ready leads | tenant-data-model, marketing-lead-qualification, marketing-to-sales-handover | sales-ready-lead-watcher |
won-opportunity-handover-watcher | Act on won opportunities with no Delivery handover | tenant-data-model, sales-process, sales-to-delivery-handover | won-opportunity-handover-watcher |
incoming-rfp-watcher | Ingest new RFPs from Sales folder; draft offers; stop at approval | tenant-data-model, crm-field-mapping, rfp-handling | incoming-rfp-watcher |
delivery-blocker-watcher | Chase delivery quality-gate failures | tenant-data-model, delivery-process, sales-to-delivery-handover | delivery-blocker-watcher |
support-sla-watcher | Escalate support cases past sla_due_at | tenant-data-model, support-process | support-sla-watcher |
ai-engagement-followup-watcher | Chase stale AI-adoption interviews and unscored use cases | ai-adoption-data-model | ai-engagement-followup-watcher |