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Agent skill

Mz Platform Checks

by MaterializeInc in MaterializeInc/materialize

Create/modify/debug platform check. An agent skill from MaterializeInc/materialize.

Custom licenceAuto-check passedDatabases

Install Mz Platform Checks

skills CLI
$ npx skills add MaterializeInc/materialize --skill mz-platform-checks -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install MaterializeInc/materialize mz-platform-checks --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/mz-platform-checks .claude/skills/mz-platform-checks && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
mz-platform-checks
GitHub stars
6.4k
Token cost
~1.6k tokens
SKILL.md length
404 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
Custom licence

At a glance

Create/modify/debug platform check. An agent skill from MaterializeInc/materialize.

  • Works in 8 steps: Naming: Prefix ALL object names with a… → manipulate() returns exactly 2 elements:… → validate() is idempotent: It may run… → …
  • Databases work in your project
  • SKILL.md covers Key Concepts, Where Checks Live, Anatomy of a Check and Execution Order in a Scenario, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mz Platform Checks is an agent skill from MaterializeInc/materialize. Create/modify/debug platform check. Trigger: "platform check", "platform-checks", "upgrade check", "restart check", or writing Check class testing feature survival across restarts/upgrades. Also edits in misc/python/materialize/checks/allchecks/.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases. It works with Python, PostgreSQL, SQL and Apache Kafka. The repository describes itself as: The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL.

When your agent uses it

  • Databases work in your project

Example prompts

  • “platform check”
  • “platform-checks”
  • “upgrade check”
  • “/mz-platform-checks”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Naming: Prefix ALL object names with a unique string (e.g., my_feature_) to avoid collisions with other checks running in the same Mz…
  2. manipulate() returns exactly 2 elements: The framework asserts this.
  3. validate() is idempotent: It may run multiple times. Use TEMPORARY objects or DROP at end.
  4. Create objects in manipulate, not just initialize: This tests that DDL works after restarts/upgrades.
  5. Create derived objects on both old and new base objects: e.g., a materialized view on a table from initialize AND on a table from…
  6. Exercise full SQL syntax breadth: Test every WITH option, every variant of the feature.
  7. Ingest data in every phase: Ensure data flows during restarts/upgrades.
  8. Use dedent() on all testdrive strings: Required for proper testdrive parsing.

What it can do on your machine

Read from SKILL.md and the folder at commit b760ecc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mz Platform Checks loads about 1.6k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 404 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 404 words (~1,589 tokens).

“The Platform Checks framework is "write once, run everywhere" - a single test validates a feature across multiple scenarios (restarts, upgrades, etc.).”

— opening of SKILL.md by MaterializeInc, Custom licence
name
mz-platform-checks

Read the full SKILL.md on GitHub

Files

Just SKILL.md in .agents/skills/mz-platform-checks of MaterializeInc/materialize.

Open the folder on GitHubat commit b760ecc

Compare with similar skills

Mz Platform Checks next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Mz Platform Checks compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Mz Platform Checks this skillMaterializeInc/materialize6.4k—~1.6kAutomated safety check: PassCustom licence
Chdb SQLvemetric/vemetric3941 repos~1.2kAutomated safety check: PassApache-2.0
Cloudsql Idle Connection Timeoutdivinevideo/divine-mobile266—~1.1kAutomated safety check: PassMPL-2.0
Psycopg2 Like Percent Escapedivinevideo/divine-mobile266—~1.1kAutomated safety check: PassMPL-2.0
Chdb Datastorevemetric/vemetric3942 repos~1.4kAutomated safety check: PassApache-2.0
SQL Database Support for pRESTprest/prest4.6k—~1.6kAutomated safety check: PassMIT

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  • Mz Commit

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    Trigger: "commit", "prepare commit", "create PR", "push", "open pull request", or mentions committing, pre-commit checks, pull requests in Materialize.

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  • Mz Dbt Release

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    Cut a dbt-materialize PyPI release: bump the version in version.py and setup.py, date the Unreleased CHANGELOG entry, and open the release PR with a Ship: <url body.

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  • Mz Debug CI

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Works with

Categories

Questions about Mz Platform Checks

What does Mz Platform Checks do?

Create/modify/debug platform check. An agent skill from MaterializeInc/materialize. Mz Platform Checks is an agent skill from MaterializeInc/materialize. Create/modify/debug platform check.

When should I use Mz Platform Checks?

Mz Platform Checks fits situations like: databases work in your project.

How do I install Mz Platform Checks in Claude Code?

Run `npx skills add MaterializeInc/materialize --skill mz-platform-checks -a claude-code`. Or copy the skill folder (.agents/skills/mz-platform-checks in MaterializeInc/materialize) into .claude/skills/mz-platform-checks in your project. Claude Code loads it when a task matches its description.

How do I install Mz Platform Checks in Codex?

Run `npx skills add MaterializeInc/materialize --skill mz-platform-checks -a codex`. Or copy the skill folder (.agents/skills/mz-platform-checks in MaterializeInc/materialize) into .agents/skills/mz-platform-checks in your project. Codex loads it when a task matches its description.

Can I use Mz Platform Checks in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MaterializeInc/materialize --skill mz-platform-checks -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mz-platform-checks, .gemini/skills/mz-platform-checks, .github/skills/mz-platform-checks and .opencode/skills/mz-platform-checks in your project.

What does Mz Platform Checks need to run?

SKILL.md names no scripts, command-line tools or credentials: Mz Platform Checks is instructions for the agent only. Our summary lists: Python 3.

Does Mz Platform Checks access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Mz Platform Checks safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Mz Platform Checks use?

Mz Platform Checks has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Mz Platform Checks use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Mz Platform Checks?

Skills that share tags, products or a category with Mz Platform Checks: Chdb SQL (vemetric/vemetric, 394 stars), Cloudsql Idle Connection Timeout (divinevideo/divine-mobile, 266 stars), Psycopg2 Like Percent Escape (divinevideo/divine-mobile, 266 stars) and Chdb Datastore (vemetric/vemetric, 394 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mz Platform Checks?

MaterializeInc (a GitHub organization) maintains it in MaterializeInc/materialize, which has 6,377 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 8, 2026.

Source: MaterializeInc/materialize on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.