add-agent-playbooks
Add Agent Playbooks
Bring an existing Python agent to one verified Playbook-backed turn, then finish the requested content migration or integration. FAQs supply published answers; Skills supply procedures loaded separately from discovery previews. The application owns response policy, tool permissions, and approval of actions.
1. Orient and choose the behavior
Find the model call, tool registration, framework/version, and existing policy or procedure sources. Preserve the graph, business tools, and global response/authorization rules. Infer these decisions from the request and code; ask only about unresolved choices and state defaults used:
| Decision | Result |
|---|---|
| Which repeated tasks need procedures? | One Skill per procedure; skip when none. Move task-specific tool guidance out of prompts. |
| Which questions require approved answers? | One FAQ per approved answer; skip when none. |
| Which audiences use the content? | One audience: no attribute or filter. Several: matching attributes on content and a trusted runtime audience. |
| Should uncovered answers be submitted for review? | Default no. Yes: choose automatic uncovered proposals or an application-owned quality/privacy gate; preserve existing gates. |
| Where does the content live today? | Convert relevant prompt text, docs, or retrieved content into versioned files. Retain authoritative sources. |
Prefer progressive disclosure when the agent can execute tools; use score-based hooks otherwise. Define clarification, escalation, and outage behavior: approved-only answers need an explicit policy for insufficient content.