Scope and Redaction Note
This playbook is for automating AI-agent operations, content operations, and site-health loops. It uses public examples and placeholders only. Do not automate publication of real tokens, webhook URLs, private logs, customer content, account identifiers, internal hostnames, or commercial promises.
Automation Ladder
- Read-only checks: sitemap, link audit, source monitoring, analytics snapshots, and health probes.
- Owner-facing report: concise findings, confidence grades, risks, and recommended next action.
- Draft artifact: outline, FAQ, source list, internal links, and distribution copy in a reviewable location.
- Approved content write: update public pages only after the owner approves the asset and scope.
- Approved deploy: deploy the smallest changed files, keep backups, run smoke tests, and record state.
What To Automate First
Site Health
Run sitemap checks, page audits, broken-link scans, metadata checks, and post-deploy smoke tests.
Signal Radar
Monitor official docs, changelogs, GitHub releases, standards pages, and vendor blogs before social feeds.
Analytics Review
Use Umami for real pageviews, Search Console for organic discovery, and logs only for debugging.
Draft Packs
Generate outlines, FAQ blocks, source lists, internal links, and distribution copy without publishing automatically.
Codex Automation Modes
- Thread automation: use when the work should wake up inside the same conversation and preserve context.
- Standalone/project automation: use when each run should report as a separate background task.
- Worktree run: use for Git repositories when automation may create diffs and should not collide with active work.
- Local-project run: use only when the automation intentionally works in the active checkout.
- Skill-driven run: use a skill when the automation should follow a reusable workflow with references and scripts.
- Hook guardrail: use hooks for lifecycle checks such as prompt scanning, command review, and stop-time validation.
Prompt Contract
A durable automation prompt should say what to check, what evidence to trust, what to ignore, what to output, and when to ask for owner approval.
# Task
Run the daily AI-agent operations check for <site-or-project>.
# Inputs
- Static health commands:
- Analytics source:
- Search/source list:
- Current priority asset:
# Trust policy
- A: official docs, release notes, standards, GitHub releases
- B: vendor blogs and maintained repositories
- C: community posts with cross-checks
- D: social/video early signals only
# Output
- Health status
- New facts with confidence
- Recommended action
- Draft asset if useful
- Owner approval needed
# Hard stops
- Do not publish secrets.
- Do not edit public pages without approval.
- Do not deploy without approval.
- Do not make commercial promises.Approval Gates
- Automate collection, analysis, and draft generation by default.
- Require owner approval before editing public pages, changing analytics, deploying, pricing services, or claiming customer outcomes.
- Keep all generated drafts reviewable; never hide the source list or risk notes.
- Record state after a production change so the next automation run knows what shipped.
Failure Modes
- News-feed drift: the automation summarizes everything and learns nothing. Fix with confidence grades and "why it matters."
- Silent stale data: the automation ignores analytics lag. Fix by labeling unavailable or delayed sources.
- Prompt sprawl: every run adds a new format. Fix with a stable report shape and small improvements.
- Unsafe autonomy: background jobs edit live files without review. Fix with worktrees, approval gates, and deployment smoke tests.
OpenClaw Codex Site Ops Pattern
For this site, the automation loop is deliberately conservative: daily reports can collect facts, inspect health, query analytics, recommend English assets, and generate draft packs. Public site changes and Tencent Cloud deployment still require owner approval.
FAQ
What should AI agent teams automate first?
Start with read-only health checks, signal collection, analytics summaries, and draft briefs. These create value without risking unintended production changes.
Should automations edit production content directly?
Not by default. Public content changes, deployments, pricing, and customer claims should stay behind explicit owner approval.
When should an automation use a worktree?
Use a worktree when the run may create diffs in a Git repository and you want those changes isolated from unfinished local work.
Where do hooks fit?
Hooks are lifecycle guardrails. They are useful for command review, prompt scanning, stop-time checks, and validation around agent actions.
Audit Before Expanding Autonomy
If a workflow is ready to move beyond read-only checks and draft packs, review permissions, recovery, analytics, and owner approval gates before allowing more automated actions.