SQL Database Support for pREST
prest/prest
Guides classifying, gap-analyzing and scaffolding support for a new SQL database in pREST, from Postgres-compatible variants to entirely new dialects.
Add/modify/debug Materialize perf benchmark scenarios. An agent skill from MaterializeInc/materialize.
Install Mz Benchmark
$ npx skills add MaterializeInc/materialize --skill mz-benchmark -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MaterializeInc/materialize mz-benchmark --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/mz-benchmark .claude/skills/mz-benchmark && rm -rf skills-srcUse ~/.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/
Install the "mz-benchmark" agent skill from https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmark into .claude/skills/mz-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mz-benchmark", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmarkType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add MaterializeInc/materialize --skill mz-benchmark -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MaterializeInc/materialize mz-benchmark --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/mz-benchmark .agents/skills/mz-benchmark && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mz-benchmark" agent skill from https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmark into .agents/skills/mz-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mz-benchmark", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MaterializeInc/materialize --skill mz-benchmark -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MaterializeInc/materialize mz-benchmark --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/mz-benchmark .cursor/skills/mz-benchmark && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mz-benchmark" agent skill from https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmark into .cursor/skills/mz-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mz-benchmark", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/MaterializeInc/materialize.git --path .agents/skills/mz-benchmark--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add MaterializeInc/materialize --skill mz-benchmark -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MaterializeInc/materialize mz-benchmark --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/mz-benchmark .gemini/skills/mz-benchmark && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mz-benchmark" agent skill from https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmark into .gemini/skills/mz-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mz-benchmark", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install MaterializeInc/materialize mz-benchmarkInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add MaterializeInc/materialize --skill mz-benchmark -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/mz-benchmark .github/skills/mz-benchmark && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mz-benchmark" agent skill from https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmark into .github/skills/mz-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mz-benchmark", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MaterializeInc/materialize --skill mz-benchmark -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MaterializeInc/materialize mz-benchmark --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaterializeInc/materialize.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/mz-benchmark .opencode/skills/mz-benchmark && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mz-benchmark" agent skill from https://github.com/MaterializeInc/materialize/tree/main/.agents/skills/mz-benchmark into .opencode/skills/mz-benchmark/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mz-benchmark", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
mz-benchmark- GitHub stars
- 6.4k
- Token cost
- ~2.8k tokens
- SKILL.md length
- 621 words
- Files
- 1
- Skills in repo
- 15
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Add/modify/debug Materialize perf benchmark scenarios. An agent skill from MaterializeInc/materialize.
- Works in 3 steps: Feature Benchmark (Micro-benchmarks) → Scalability Test (SQL Throughput Under… → Parallel Benchmark (Sustained Performance)
- Tasks that involve SQL
- SKILL.md covers Decision Guide, 1. Feature Benchmark…, 2. Scalability Test (SQL… and 3. Parallel Benchmark…
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Mz Benchmark is an agent skill from MaterializeInc/materialize. Add/modify/debug Materialize perf benchmark scenarios. Three frameworks: Feature Benchmark (single-op micro), Scalability Test (SQL throughput under concurrency), Parallel Benchmark (sustained latency via scenarios.py). Trigger: "benchmark", "feature benchmark", "scalability test", "parallel benchmark", "performance regression", "micro-benchmark", "TPS", "latency test", or edits in featurebenchmark/scenarios/, scalability/workload/workloads/, parallelbenchmark/scenarios.py. Note: measurement, not panic-stress…
Its SKILL.md is about 2.8k 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, covering SQL. It works with SQL, Apache Kafka and PostgreSQL. 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
- Tasks that involve SQL
Example prompts
- “benchmark”
- “feature benchmark”
- “scalability test”
- “/mz-benchmark”
Requirements
- Python 3
- Docker
Workflow steps
3 steps, taken from the step headings in SKILL.md.
- Feature Benchmark (Micro-benchmarks)
- Scalability Test (SQL Throughput Under Concurrency)
- Parallel Benchmark (Sustained Performance)
What it can do on your machine
Read from SKILL.md and the folder at commit 80f0437. 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 Benchmark loads about 2.8k tokens when it runs. Until then it costs about 139 tokens; SKILL.md has 621 words of instructions outside code blocks.
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 621 words (~2,833 tokens).
“Materialize has some benchmark frameworks targetting local Docker, each suited to different performance concerns. Choose the right one based on what you're measuring.”
- name
- mz-benchmark
Files
Just SKILL.md in .agents/skills/mz-benchmark of MaterializeInc/materialize.
Open the folder on GitHubat commit 80f0437
Compare with similar skills
Mz Benchmark 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mz Benchmark this skillMaterializeInc/materialize | 6.4k | — | ~2.8k | Automated safety check: Pass | Custom licence | |
| SQL Database Support for pRESTprest/prest | 4.6k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Chdb SQLvemetric/vemetric | 394 | 1 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Schema Explorationtimescale/pg-aiguide | 1.9k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Dingtalk AitableDingTalk-Real-AI/dingtalk-workspace-cli | 3.2k | — | ~5.4k | Automated safety check: Pass | Apache-2.0 | |
| Sql2erystemsrx/sql_to_ER | 188 | — | ~1.1k | Automated safety check: Pass | AGPL-3.0 |
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More from MaterializeInc/materialize
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Verify a release candidate on the Grafana dashboards and sign off in release.
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.
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.
Mz Debug CI
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Investigate CI failures on PR via gh + Buildkite MCP or bk CLI.
Mz Limits Test
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Mz Parallel Workload
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Extend parallel-workload stress framework: random SQL concurrently to catch panics + unexpected errors (not perf — see mz-benchmark).
Related
Works with
Categories
Questions about Mz Benchmark
What does Mz Benchmark do?
Add/modify/debug Materialize perf benchmark scenarios. An agent skill from MaterializeInc/materialize. Mz Benchmark is an agent skill from MaterializeInc/materialize. Add/modify/debug Materialize perf benchmark scenarios.
When should I use Mz Benchmark?
Mz Benchmark fits situations like: tasks that involve SQL.
How do I install Mz Benchmark in Claude Code?
Run `npx skills add MaterializeInc/materialize --skill mz-benchmark -a claude-code`. Or copy the skill folder (.agents/skills/mz-benchmark in MaterializeInc/materialize) into .claude/skills/mz-benchmark in your project. Claude Code loads it when a task matches its description.
How do I install Mz Benchmark in Codex?
Run `npx skills add MaterializeInc/materialize --skill mz-benchmark -a codex`. Or copy the skill folder (.agents/skills/mz-benchmark in MaterializeInc/materialize) into .agents/skills/mz-benchmark in your project. Codex loads it when a task matches its description.
Can I use Mz Benchmark 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-benchmark -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-benchmark, .gemini/skills/mz-benchmark, .github/skills/mz-benchmark and .opencode/skills/mz-benchmark in your project.
What does Mz Benchmark need to run?
SKILL.md names no scripts, command-line tools or credentials: Mz Benchmark is instructions for the agent only. Our summary lists: Python 3; Docker.
Does Mz Benchmark 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 Benchmark 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 Benchmark use?
Mz Benchmark 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 Benchmark use?
About 2.8k tokens (SKILL.md is roughly 11k 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 Benchmark?
Skills that share tags, products or a category with Mz Benchmark: SQL Database Support for pREST (prest/prest, 4.6k stars), Chdb SQL (vemetric/vemetric, 394 stars), Schema Exploration (timescale/pg-aiguide, 1.9k stars) and Dingtalk Aitable (DingTalk-Real-AI/dingtalk-workspace-cli, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mz Benchmark?
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 7, 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.