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Planetscale Webhook Automation Recommendations

Organization
planetscale
planetscale-webhook-automation-recommendations

Recommend webhook subscriptions and safe automation patterns for PlanetScale alerts, anomalies, schema recommendations, deploy requests, and agent workflows.

Overview

Publisherplanetscale
Repositoryskills
Skill nameplanetscale-webhook-automation-recommendations
Stars
136
Forks
6
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by planetscale on GitHub. Read the source before you install it.

Installation

Install the Planetscale Webhook Automation Recommendations AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/planetscale/skills/tree/main/planetscale-webhook-automation-recommendations
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/planetscale/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/planetscale-webhook-automation-recommendations .claude/skills/planetscale-webhook-automation-recommendations
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Planetscale Webhook Automation Recommendations in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Planetscale Webhook Automation Recommendations on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Planetscale Webhook Automation Recommendations is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Webhook automation recommendations

Purpose

Review and recommend PlanetScale webhooks that notify humans and trigger safe automation. Do not create or update webhooks without approval.

Webhook design principle

Webhooks may trigger automation, but automation must produce recommendations, issues, branches, or pull requests by default. It must not directly mutate production databases or production application behavior without explicit human approval.

Events to evaluate

General and Postgres

  • branch.anomaly: new Insights anomaly.
  • branch.out_of_memory: Postgres out-of-memory event.
  • branch.primary_promoted: primary failover/promotion.
  • branch.ready: branch created and ready.
  • branch.sleeping: branch sleeping.
  • branch.start_maintenance: maintenance starting.
  • cluster.storage: storage threshold or growth event.
  • database.access_request: access request.
  • branch.schema_recommendation: schema recommendation event when available.
  • webhook.test: test event.

Vitess deploy lifecycle

  • deploy_request.opened
  • deploy_request.queued
  • deploy_request.in_progress
  • deploy_request.pending_cutover
  • deploy_request.schema_applied
  • deploy_request.errored
  • deploy_request.reverted
  • deploy_request.closed
  • keyspace.storage

Recommended routing

Human alerting

Send these to incident or operations channels:

  • branch.anomaly
  • branch.out_of_memory
  • branch.primary_promoted
  • branch.start_maintenance
  • cluster.storage
  • keyspace.storage
  • deploy_request.errored
  • deploy_request.reverted

Engineering notification

Send these to Slack, Linear/Jira, or deployment channels:

  • deploy_request.opened
  • deploy_request.queued
  • deploy_request.in_progress
  • deploy_request.pending_cutover
  • deploy_request.schema_applied
  • deploy_request.closed
  • branch.schema_recommendation

Agent intake queue

Send these to an agent-safe workflow:

  • branch.anomaly
  • branch.schema_recommendation
  • deploy_request.errored
  • cluster.storage
  • keyspace.storage

Agent output may include, without approval:

  • Triage summary, probable cause, linked Insights/query patterns.
  • Recommended schema, code, Traffic Control, or operational change.
  • Pull request against application code.
  • Development branch with DDL or migration applied.
  • Open deploy request into a review-protected branch.
  • Issue or ticket.

Agent output must not cross the review gate on its own: no production deploys, PR merges, Traffic Control enforcement, credential rotation, or network changes — those require human action or a standing authorization per ../planetscale-autonomous-execution-mode/SKILL.md.

Webhook receiver requirements

Recommend only receivers that meet these requirements:

  • HTTPS endpoint.
  • Fast 2xx response; expensive work is queued asynchronously.
  • No dependency on following redirects.
  • Signature verification using PlanetScale webhook signature header and the webhook secret.
  • Idempotency by event ID or timestamp/resource tuple.
  • Dead-letter queue or retry-safe logging.
  • Human-readable audit trail.
  • Clear owner and escalation path.
  • Secret rotation procedure.

Recommended automation flows

Anomaly to PR flow

  1. Receive branch.anomaly.
  2. Verify signature.
  3. Queue job.
  4. Fetch anomaly details and relevant Insights query patterns.
  5. Locate code path by SQLCommenter tags and repository search.
  6. Classify as schema, code, Traffic Control, or unknown.
  7. Generate report and optional PR.
  8. Ask human to approve database-affecting work.

Schema recommendation to branch/deploy flow

For Vitess:

  1. Receive branch.schema_recommendation.
  2. Fetch recommendation details.
  3. Apply the DDL to a development branch.
  4. Open a pull request with fingerprint, metrics, and expected effect.
  5. Open the deploy request — the DR and PR together are the reviewable unit; opening them requires no approval.
  6. Deploy on human approval, or autonomously under a standing authorization that allowlists this deploy class (../planetscale-autonomous-execution-mode/SKILL.md).

For Postgres:

  1. Receive branch.schema_recommendation.
  2. Fetch recommendation details.
  3. Convert DDL to application migration.
  4. Test on a non-production branch and record the result in the PR.
  5. Open PR.
  6. Apply to production on merge via the deployment pipeline, or on explicit approval where no pipeline exists.

Deploy request lifecycle flow for Vitess

  • Notify when opened.
  • Validate owner and linked application PR.
  • Alert when queued or in progress.
  • Alert strongly when errored or reverted.
  • Notify pending cutover and require owner acknowledgement for gated deployments.
  • Record schema applied and correlate with application deploy.

Anti-patterns to block

Do not recommend:

  • Webhook directly runs production DDL, bypassing the PR/deploy-request workflow. (Driving the DDL through a branch, PR, and deploy request is the supported pattern, not an anti-pattern.)
  • Webhook applies schema recommendations straight to production with no reviewable artifact.
  • Webhook directly enforces Traffic Control.
  • Webhook directly changes IP restrictions.
  • Webhook directly rotates credentials.
  • Webhook posts secrets or raw SQL with literals into public Slack channels.
  • Webhook receiver ignores signature verification.
  • Webhook receiver does long-running work before returning 2xx.

Output

Return:

  • Existing webhook inventory.
  • Missing recommended subscriptions.
  • Destination quality review.
  • Signature verification status.
  • Automation opportunities.
  • Unsafe automation risks.
  • Proposed webhook changes requiring approval.

End with:

“No webhooks or automation endpoints have been created, updated, or deleted.”

Frequently asked questions

What does the Planetscale Webhook Automation Recommendations AI skill do?

Recommend webhook subscriptions and safe automation patterns for PlanetScale alerts, anomalies, schema recommendations, deploy requests, and agent workflows.

Why use Planetscale Webhook Automation Recommendations on TypingMind?

Because you install it once and use it with any model. Planetscale Webhook Automation Recommendations is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Planetscale Webhook Automation Recommendations in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/planetscale/skills/tree/main/planetscale-webhook-automation-recommendations. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Planetscale Webhook Automation Recommendations?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Planetscale Webhook Automation Recommendations?

As many as you like. As long as a model supports skills, you can use Planetscale Webhook Automation Recommendations with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Planetscale Webhook Automation Recommendations AI skill free?

Yes. It is published on GitHub by planetscale under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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