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Blog — PlanetScale

Keeping a Postgres queue healthy — PlanetScale Patterns for Postgres Traffic Control — PlanetScale Graceful degradation in Postgres — PlanetScale High memory usage in Postgres is good, actually — PlanetScale Stripe Projects partnership: Provision PlanetScale Postgres and MySQL databases from the Stripe CLI — PlanetScale Enhanced tagging in Postgres Query Insights — PlanetScale Behind the scenes: How Database Traffic Control works — PlanetScale Introducing Database Traffic Control — PlanetScale Scaling Postgres connections with PgBouncer — PlanetScale Drizzle joins PlanetScale — PlanetScale Video Conferencing with Postgres — PlanetScale Faster PlanetScale Postgres connections with Cloudflare Hyperdrive — PlanetScale Introducing the PlanetScale MCP server — PlanetScale Database Transactions — PlanetScale Postgres 18 is now available — PlanetScale Using MotherDuck with PlanetScale — PlanetScale $50 PlanetScale Metal is GA for Postgres — PlanetScale AI-Powered Postgres index suggestions — PlanetScale $5 PlanetScale is live — PlanetScale Announcing Vitess 23 — PlanetScale $50 PlanetScale Metal — PlanetScale Report on our investigation of the 2025-10-20 incident in AWS us-east-1 — PlanetScale $5 PlanetScale — PlanetScale Benchmarking Postgres 17 vs 18 — PlanetScale Larger than RAM Vector Indexes for Relational Databases — PlanetScale Partnering with Cloudflare to bring you the fastest globally distributed applications — PlanetScale Processes and Threads — PlanetScale PlanetScale for Postgres is now GA — PlanetScale Postgres High Availability with CDC — PlanetScale Announcing Neki — PlanetScale Caching — PlanetScale The principles of extreme fault tolerance — PlanetScale Announcing PlanetScale for Postgres — PlanetScale Benchmarking Postgres — PlanetScale Announcing Vitess 22 — PlanetScale The Real Failure Rate of EBS — PlanetScale IO devices and latency — PlanetScale Announcing PlanetScale Metal — PlanetScale PlanetScale Metal: There’s no replacement for displacement — PlanetScale Upgrading Query Insights to Metal — PlanetScale Automating cherry-picks between OSS and private forks — PlanetScale Database Sharding — PlanetScale Anatomy of a Throttler, part 3 — PlanetScale Introducing sharding on PlanetScale with workflows — PlanetScale Announcing Vitess 21 — PlanetScale Announcing the PlanetScale vectors public beta — PlanetScale Anatomy of a Throttler, part 2 — PlanetScale Instant deploy requests — PlanetScale Anatomy of a Throttler, part 1 — PlanetScale Increase IOPS and throughput with sharding — PlanetScale Tracking index usage with Insights — PlanetScale Faster backups with sharding — PlanetScale Building data pipelines with Vitess — PlanetScale The State of Online Schema Migrations in MySQL — PlanetScale Optimizing aggregation in the Vitess query planner — PlanetScale Dealing with large tables — PlanetScale Announcing Vitess 20 — PlanetScale Self-managed Vitess vs Managed Vitess with PlanetScale — PlanetScale Achieving data consistency with the consistent lookup Vindex — PlanetScale The MySQL adaptive hash index — PlanetScale Introducing global replica credentials — PlanetScale Profiling memory usage in MySQL — PlanetScale Summer 2023: Fuzzing Vitess at PlanetScale — PlanetScale How PlanetScale makes schema changes — PlanetScale Identifying and profiling problematic MySQL queries — PlanetScale The Problem with Using a UUID Primary Key in MySQL — PlanetScale Announcing Vitess 19 — PlanetScale PlanetScale forever — PlanetScale Introducing schema recommendations — PlanetScale Amazon Aurora Pricing: The many surprising costs of running an Aurora database — PlanetScale Three common MySQL database design mistakes — PlanetScale OAuth applications are now available to everyone — PlanetScale Deprecating the Scaler plan — PlanetScale PlanetScale branching vs. Amazon Aurora blue/green deployments — PlanetScale Databases at scale — PlanetScale Considerations for building a database disaster recovery plan — PlanetScale Working with Geospatial Features in MySQL — PlanetScale PlanetScale vs Amazon Aurora replication — PlanetScale Introducing the Vantage and PlanetScale integration — PlanetScale MySQL isolation levels and how they work — PlanetScale Introducing the schemadiff command line tool — PlanetScale $ pscale ping — PlanetScale Announcing foreign key constraints support — PlanetScale The challenges of supporting foreign key constraints — PlanetScale What is HTAP? — PlanetScale Introducing Insights Anomalies — PlanetScale Webhook security: a hands-on guide — PlanetScale Announcing the Fivetran integration — PlanetScale Introducing webhooks — PlanetScale What is MySQL replication and when should you use it? — PlanetScale Sync user data between Clerk and a PlanetScale MySQL database — PlanetScale Introducing database reports — PlanetScale Distributed caching systems and MySQL — PlanetScale What is MySQL partitioning? — PlanetScale MySQL High Availability: Connection handling and concurrency — PlanetScale Personalizing your onboarding with Markdoc — PlanetScale PlanetScale vs. Amazon Aurora — PlanetScale PlanetScale vs. Amazon RDS — PlanetScale PlanetScale is bringing vector search and storage to MySQL — PlanetScale PlanetScale Managed is now PCI compliant — PlanetScale
Automating our changelog with Cursor commands — PlanetScale
Mike Coutermarsh · 2026-01-07 · via Blog — PlanetScale

Mike Coutermarsh |

Ever since Cursor commands were released, we've been using them to find ways to shortcut common tasks at PlanetScale.

A Cursor command allows you to add slash (/actions) commands directly into Cursor. Each command guides the LLM on completing a common and repeatable workflow for you.

Updating our changelog

Each time we ship a feature or improvement at PlanetScale, we release an update on our changelog. Each changelog entry is a markdown file in a single directory checked into a Git repository.

Whenever someone wants to write a new entry, they add a markdown file, open a GitHub pull request and merge it. Shortly after, it gets published on our website and sent out on the changelog RSS feed.

Example changelog:

---
title: 'Webhook API endpoints'
createdAt: '2025-04-25'
---

We've just added new...

Each changelog follows a similar format and almost always ships after we have already written the docs for the feature.

This makes it a perfect use case for Cursor to generate. The format is specific and the context about the feature is already in our documentation repo. Cursor has everything it needs to publish for us.

Iterating to perfection

We found the easiest way to make a rule is to have Cursor create the initial version itself based on a task we just had it complete.

For example, if I recently used Cursor to update our API docs, I'd finish up the conversation by having it make it repeatable with a command in the future.

Please create a new Cursor command for the process we just went through, so that it is easy to replicate in the future for others. Call it /updateapi.

This gives you a good starting point. From there, each time you run it, you can update the command if the results aren't satisfactory. We've found it only takes a couple tweaks to get the workflow into a place that we can rely on it.

Launching from Slack

Another benefit of using commands is that they can be kicked off from the Slack bot.

Cursor changelog slackbot

This resulted in Cursor automatically opening the pull request on my behalf. All I needed to do was review and merge it.

Our changelog command

Here's an example of what our changelog command looks like.

## Create a changelog

This command creates a new changelog entry following PlanetScale's established format and style guidelines.

### Changelog Format Requirements

**File Structure:**
- Filename: `kebab-case-title.md` (descriptive, lowercase with hyphens)
- Location: `content/changelog/`

**Frontmatter:**
---
title: 'Human-readable title'
category: 'Feature|Enhancement|Bug Fix' # Optional
createdAt: 'YYYY-MM-DD' # Current date, sometimes with time
---

**Content Guidelines:**
- **Concise**: 1-3 paragraphs maximum
- **Consistent**: Examine recent similar changelogs to understand format
- **Simple language**: Avoid jargon, be conversational
- **Human tone**: Informal, not corporate-sounding
- **Avoid "programmatically"**: Do not use this word in changelog entries
- **Clear scope**: Explicitly mention if feature is Vitess-only or Postgres-only
- **External links**: Link to relevant documentation when available
- **Screenshots**: Include if available, using `![Alt text](./filename.png)` format

**Common Patterns:**
- Start with what was added/changed
- Explain the benefit or use case
- Include links to documentation with `**[Read more](/docs/path)**`
- For API features, link to API docs
- For UI features, include screenshots
- Use bullet points for multiple related items