Build crash-safe AI agents on AgentKit and step.ai — durable tool calls, human-in-the-loop approval, realtime progress, and when not to reach for an agent loop at all.
PlanetScale Safe OrchestratorSkill
Summary
The master skill in PlanetScale's official pack: runs a full read-only best-practices assessment of a database or org, then produces one evidence-backed report.
Features
- Runs every assessment phase in order and emits one unified report
- Read-only by default; mutations need approval of a named change set
- Covers branches, safe migrations, backups, roles, pooling, Insights, webhooks and Traffic Control
- Maps expensive query patterns back to the code that produces them when the repo is present
- Every claim carries the command that produced it; every recommendation an ID, gate and rollback
- Grounds CLI and API usage in planetscale.com/docs/llms.txt and the OpenAPI spec
Install This Skill
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Skill Content
Usage Instructions
Learn how to use this skill with different AI agents.
Example Usage
Run the full PlanetScale best-practices assessment on my-org/my-db. My application repository is in this workspace: include query attribution and instrumentation recommendations for it. Read-only: propose everything, change nothing.
Description
PlanetScale ships an official skill pack that turns a coding agent into a database reviewer, and this is its entry point. Ask for a best-practices assessment and this skill loads the sub-skills in order, accumulates evidence from each phase, and emits a single unified recommendations report.
Read-only is the default, and it is a contract
The safety section is not advisory. The agent may inspect configuration, branches, query telemetry, recommendations, webhooks, roles, backups, traffic budgets and your repository code. It may not mutate PlanetScale, the database, the repository, network posture, credentials, schema, production traffic controls or automation endpoints without explicit approval of a named change set. When a step is ambiguous, the instruction is to stop and add the item to the proposed change set rather than execute it.
There is exactly one way past that, and it is deliberately hard to trip: the operator explicitly acknowledges the risk and names a scope, at which point the autonomous-execution sub-skill takes over with its own halt discipline. "Go ahead" does not qualify.
What one pass covers
Inventory and engine review (Vitess or PlanetScale Postgres), branch topology and schema-change workflow, safe migrations and deploy requests, backups and restore posture, roles and credentials, connection pooling and network configuration, Query Insights behaviour, anomalies, SQL comment and query-tag coverage, open schema recommendations, webhooks, Traffic Control, and — when the application repository is in the workspace — codebase instrumentation.
That last one is where the pack earns its keep. With the repo in view the agent can map an expensive query pattern in Insights back to the route, job or ORM call that produces it, rather than reporting an anonymous slow query.
Evidence, not assertions
Every claim in the report carries the command that produced it; every recommendation carries a measured finding, a gate and a rollback path, and an ID you approve by name. Tooling failures go in an internal run log, never in the customer-facing report. The skill grounds its CLI and API usage in planetscale.com/docs/llms.txt and the published OpenAPI spec instead of guessing at command syntax.
Works with any agent that reads SKILL.md — Cursor, Claude Code, and anything following the open agent-skills convention. Sub-skills must stay siblings on disk; they reference each other by relative path.
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