Keeper Stress Analysis
ClickHouse/ClickHouse
Analyze ClickHouse Keeper stress-test results from play.clickhouse.com / keeperstresstests data warehouse.
List all connected datasets with their status, table counts, and last analysis date.
$ npx skills add ai-analyst-lab/ai-analyst --skill datasets -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ai-analyst-lab/ai-analyst datasets --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/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/datasets .claude/skills/datasets && 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 "datasets" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasets into .claude/skills/datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datasets", 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/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasetsType 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 ai-analyst-lab/ai-analyst --skill datasets -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ai-analyst-lab/ai-analyst datasets --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/datasets .agents/skills/datasets && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "datasets" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasets into .agents/skills/datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datasets", 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 ai-analyst-lab/ai-analyst --skill datasets -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ai-analyst-lab/ai-analyst datasets --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/datasets .cursor/skills/datasets && 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 "datasets" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasets into .cursor/skills/datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datasets", 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/ai-analyst-lab/ai-analyst.git --path .claude/skills/datasets--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 ai-analyst-lab/ai-analyst --skill datasets -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ai-analyst-lab/ai-analyst datasets --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/datasets .gemini/skills/datasets && 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 "datasets" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasets into .gemini/skills/datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datasets", 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 ai-analyst-lab/ai-analyst datasetsInstalls 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 ai-analyst-lab/ai-analyst --skill datasets -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/datasets .github/skills/datasets && 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 "datasets" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasets into .github/skills/datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datasets", 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 ai-analyst-lab/ai-analyst --skill datasets -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ai-analyst-lab/ai-analyst datasets --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/datasets .opencode/skills/datasets && 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 "datasets" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/datasets into .opencode/skills/datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "datasets", 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.
datasetsList all connected datasets with their status, table counts, and last analysis date.
Datasets is an agent skill from ai-analyst-lab/ai-analyst. List all connected datasets with their status, table counts, and last analysis date. Use this skill whenever the user invokes /datasets, or asks questions like "what datasets do I have?", "show me my data sources", "list datasets", "which datasets are connected?", "what data is available?", "show all datasets", "what datasets can I analyze?", "view my datasets", "what data sources are set up?", or any request to see what datasets exist in the system. Also trigger when users mention "switch dataset", "change…
Its SKILL.md is about 1k 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. The repository describes itself as: AI Product Analyst — Claude Code-powered data analysis toolkit. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 52c0744. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Datasets loads about 1k tokens when it runs. Until then it costs about 212 tokens; SKILL.md has 357 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.
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.
The full file from ai-analyst-lab/ai-analyst at commit 52c0744, republished under its MIT licence (© ai-analyst-lab). 357 words, ~1,008 tokens.
.claude/skills/datasets/SKILL.md (or your agent's skills folder).List all connected datasets with their status, table counts, and last analysis date.
Invoke as /datasets when the user wants to see what datasets are available.
The system supports two discovery paths:
Path A: Registry-first (preferred)
data_sources.yaml to get the official list of registered sourcesPath B: Brain-first (fallback when registry is empty)
data_sources.yaml is empty or missing, scan .knowledge/datasets/ directorymanifest.yaml to get connection details and metadataUse whichever path yields results. Many installations have datasets in .knowledge/datasets/ but an empty data_sources.yaml registry — this is normal during initial setup or when datasets are added manually.
Read .knowledge/active.yaml to determine which dataset is currently active.
For each discovered dataset (whether from registry or directory scan), read .knowledge/datasets/{name}/manifest.yaml to get:
display_name — human-readable nameconnection.type — connection type (csv, duckdb, postgres, snowflake, bigquery, databricks, redshift, mssql, mysql)connection.database or other connection-specific fieldssummary.table_count — number of tablessummary.date_range — temporal coverage (if available)summary.row_counts — per-table row counts (if profiled)summary.last_updated — when manifest was last writtenIf a manifest is missing or incomplete, show what you can determine from the directory structure and note that the dataset needs profiling.
Connected Datasets:
* your_dataset (active)
Your Dataset Name — {table_count} tables, {date_range}
Connection: {type} ({database})
Analyses: 0
- {other_dataset}
{display_name} — {table_count} tables, {date_range}
Connection: {type} ({details})
Analyses: {count}
Commands:
/switch-dataset {name} — switch active dataset
/connect-data — connect a new dataset
/data — inspect active dataset schemaMark the active dataset with *. Mark others with -.
data_sources.yaml is empty but .knowledge/datasets/ has content, scan the directory and show what's available — this is a normal state during development or manual dataset setup© ai-analyst-lab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/datasets of ai-analyst-lab/ai-analyst.
Open the folder on GitHubat commit 52c0744
Datasets 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 |
|---|---|---|---|---|---|---|
| Datasets this skillai-analyst-lab/ai-analyst | 304 | — | ~1k | Automated safety check: Pass | MIT | |
| Keeper Stress AnalysisClickHouse/ClickHouse | 50k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| Perf ComparisonClickHouse/ClickHouse | 50k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Patch Release CheckClickHouse/ClickHouse | 50k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Evolving The Data ModelTriliumNext/Trilium | 38k | — | ~2.1k | Automated safety check: Pass | AGPL-3.0 | |
| Hybrid Cloud Outboxesgetsentry/sentry | 46k | — | ~4.8k | Automated safety check: Pass | Custom licence |
ClickHouse/ClickHouse
Analyze ClickHouse Keeper stress-test results from play.clickhouse.com / keeperstresstests data warehouse.
ClickHouse/ClickHouse
Evaluate ClickHouse performance test results from existing CI/dashboard data or local perf.py runs.
ClickHouse/ClickHouse
Check whether ClickHouse's supported versions (last 3 majors + latest LTS) have recent stable patch releases, diagnose why the scheduled AutoReleases pipeline failed, and identify which releases…
TriliumNext/Trilium
A skill your agent uses when adding a DB migration or a new column/field to a Becca entity in Trilium ("add a migration", "new column on notes/attributes", "ALTER TABLE", "add a field to…
getsentry/sentry
Guide for creating and maintaining outbox-based eventually consistent operations in Sentry.
microsoft/garnet
Selects Garnet spin-wait policies based on the slow-path cost.
ai-analyst-lab/ai-analyst
Never present a metric or number in isolation; anchor every number to a comparison (prior period, benchmark, or another segment) or state that none is available.
ai-analyst-lab/ai-analyst
Retrieve proven SQL patterns, table cheatsheets, and join patterns from .knowledge/query-archaeology/ so past work gets reused.
ai-analyst-lab/ai-analyst
Save completed analyses to the knowledge system's analysis archive for future reference.
ai-analyst-lab/ai-analyst
Verify Google Workspace MCP authentication at the start of any session that needs Google APIs (Docs, Slides, Drive).
ai-analyst-lab/ai-analyst
Causal inference toolkit for when experiments are not possible: estimate treatment effects from observational data with assumption checks and mandatory caveats.
ai-analyst-lab/ai-analyst
Standardized workflow for uploading local chart PNGs to Google Drive and making them available for insertion into Google Docs and Slides.
Categories
List all connected datasets with their status, table counts, and last analysis date. Datasets is an agent skill from ai-analyst-lab/ai-analyst. List all connected datasets with their status, table counts, and last analysis date.
Datasets fits situations like: the user invokes /datasets; asks questions like what datasets do I have?; show me my data sources; which datasets are connected?.
Run `npx skills add ai-analyst-lab/ai-analyst --skill datasets -a claude-code`. Or copy the skill folder (.claude/skills/datasets in ai-analyst-lab/ai-analyst) into .claude/skills/datasets in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ai-analyst-lab/ai-analyst --skill datasets -a codex`. Or copy the skill folder (.claude/skills/datasets in ai-analyst-lab/ai-analyst) into .agents/skills/datasets in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ai-analyst-lab/ai-analyst --skill datasets -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/datasets, .gemini/skills/datasets, .github/skills/datasets and .opencode/skills/datasets in your project.
SKILL.md names no scripts, command-line tools or credentials: Datasets is instructions for the agent only.
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.
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.
Datasets is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1k tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Datasets: Keeper Stress Analysis (ClickHouse/ClickHouse, 50k stars), Perf Comparison (ClickHouse/ClickHouse, 50k stars), Patch Release Check (ClickHouse/ClickHouse, 50k stars) and Evolving The Data Model (TriliumNext/Trilium, 38k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ai-analyst-lab (a GitHub organization) maintains it in ai-analyst-lab/ai-analyst, which has 304 GitHub stars. The repository holds 43 skills in this directory. The repository was last updated on September 30, 2026.
Source: ai-analyst-lab/ai-analyst on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.