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Postgresql Planning

OrganizationPopular
amplifthq
postgresql-planning

Plan and implement OpenMeld PostgreSQL business persistence, schemas and migrations, transactions, Hyperdrive access, and data cutover. Use for the shared relational database transition or PostgreSQL work; not for unrelated D1 performance fixes or OpenConnector's upstream database.

Overview

Publisheramplifthq
Repositoryopenmeld
Skill namepostgresql-planning
Stars
1.4K
Forks
81
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 amplifthq on GitHub. Read the source before you install it.

Installation

Install the Postgresql Planning 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/amplifthq/openmeld/tree/main/.agents/skills/postgresql-planning
  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/amplifthq/openmeld.git /tmp/openmeld
mkdir -p .claude/skills
cp -r /tmp/openmeld/.agents/skills/postgresql-planning .claude/skills/postgresql-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Postgresql Planning 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 Postgresql Planning 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 Postgresql Planning 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.

OpenMeld PostgreSQL Planning

All OpenMeld databases belong to the Amplift PlanetScale organization (amplift), never the operator's personal organization. Pass --org amplift explicitly; login defaults are not the resource owner.

The architecture is decided: Cloudflare Hyperdrive connects Workers to PlanetScale PostgreSQL. Start from current source, not a new vendor comparison or the superseded D1 capacity threshold. Production has used PostgreSQL since the 2026-10-04 cutover. Shared staging reuses openmeld-postgresql-stg through its own Hyperdrive binding and the guarded pnpm staging:deploy workflow. The former staging D1 database is retained for historical test-data inspection. Use standard PlanetScale Postgres for this foundation. Neki preview enrollment does not change the chosen engine or authorize a sharded database migration. The staging/local baseline is PostgreSQL 18 at the latest supported stable minor. Use older versions only for a demonstrated compatibility constraint. Production capacity changes require measured demand. Keep capacity stable while isolating code-path regressions; use the current workflow's metrics and query plans before recommending a larger machine.

Shortest useful start

  1. Read physical database ownership and the applicable section of the single PostgreSQL workflow.
  2. Run pnpm pg plan to see exact targets and migration checksums. Check tooling/postgresql/resources.json; a planned name is not a created resource.
  3. Read the touched business owner's source, schema and contracts. Define who writes each fact and which readers need a transaction. Do not recreate RuntimeCoordinator authority, Space Durable Object state, or R2 file bodies.
  4. Implement in the existing owning package. Use standard PostgreSQL SQL and the supported pg driver; do not build a D1 API emulator or a cross-database framework. Preserve externally visible IDs and shared schemas.
  5. Run pnpm pg:check for database infrastructure changes. For business work, add the smallest real PostgreSQL behavior checks for its failure boundary, then exercise affected consumers. Local infrastructure acceptance is not proof of cloud connectivity, production scale, or completed business migration.

Decisions that change implementation

  • Application Hyperdrive caching is disabled. Transactions use one client from BEGIN through COMMIT/ROLLBACK. Hyperdrive transaction pooling cannot preserve session settings, temporary tables, or session advisory locks between queries.
  • Migrations and backup tools use the direct TLS endpoint on port 5432. A single migration owner and PostgreSQL advisory lock serialize changes.
  • Keep PostgreSQL baseline/migrations under packages/db/postgresql/migrations. Never convert or edit already-applied D1 history in place. Review generated SQL for SQLite assumptions, timestamp units, JSON, ordering, conflict behavior, indexes, constraints and affected query plans.
  • Runtime roles receive only owning-schema/table grants. No default postgres, broad all-data roles, CREATE, TRUNCATE, role management or migration ledger access. Tenant authorization remains an explicit owner contract, not a schema name.
  • Use the workflow's exact target and Doppler allowlist. No credentials in Git, logs, chat, command arguments, or ordinary development environments.
  • Retain historical test data where practical, but synthetic staging acceptance does not authorize exporting production data into staging.

Before applying or cutting over

Use the workflow's migration and cutover checklist rather than copying it here. Check source identity, target identity, immutable migration checksums, lock ownership, runtime grants, restore evidence, mixed-version consumers and one data authority. A completed resource creation is not a completed migration.

Stop the affected operation on a mismatched environment/branch, unknown owner, applied migration drift, failed restore, unresolved production writers, exposed credentials, or missing tenant authorization. After PostgreSQL accepts new business writes, reverting the binding to old D1 would lose data: freeze and reconcile under the recovery plan. New legal agreements and payment/identity challenges require the human. Do not request approval again for already authorized, bounded infrastructure setup.

Frequently asked questions

What does the Postgresql Planning AI skill do?

Plan and implement OpenMeld PostgreSQL business persistence, schemas and migrations, transactions, Hyperdrive access, and data cutover. Use for the shared relational database transition or PostgreSQL work; not for unrelated D1 performance fixes or OpenConnector's upstream database.

Why use Postgresql Planning on TypingMind?

Because you install it once and use it with any model. Postgresql Planning 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 Postgresql Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/amplifthq/openmeld/tree/main/.agents/skills/postgresql-planning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Postgresql Planning?

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 Postgresql Planning?

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

Is the Postgresql Planning AI skill free?

Yes. It is published on GitHub by amplifthq 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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