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Official agent skill

Authoring Data Quality Checks

by PostHog in PostHog/posthog

Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential…

OfficialCustom licenceAuto-check passedData & Analytics

Install Authoring Data Quality Checks

skills CLI
$ npx skills add PostHog/posthog --skill authoring-data-quality-checks -a claude-code

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

GitHub CLI
$ gh skill install PostHog/posthog authoring-data-quality-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/PostHog/posthog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/products/data_quality/skills/authoring-data-quality-checks .claude/skills/authoring-data-quality-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
authoring-data-quality-checks
GitHub stars
40k
Token cost
~2.8k tokens
SKILL.md length
1,442 words
Files
1
Skills in repo
252
Repo updated
First seen
Licence
Custom licence

At a glance

Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential…

  • Works in 3 steps: posthog:data-quality-check-create → posthog:data-quality-check-run — returns… → Poll…
  • Asked to test a model
  • SKILL.md covers Before you write anything: look, Choosing checks, Checks on PostHog tables and Checks on catalog metrics, plus 4 more sections
  • Calls dbt

What it does

Authoring Data Quality Checks is an agent skill from PostHog/posthog, published by the product's own GitHub organization. Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential integrity, row-count bounds, freshness, and custom HogQL. Metrics support custom SQL checks only. Use when asked to test a model, validate a view, check for nulls or duplicates, add data quality checks, find out why a number looks wrong, or judge whether a warehouse table is trustworthy before using it in an analysis. To…

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 Data & Analytics, covering Data cleaning and Data pipelines and ETL. It works with dbt, PostHog and SQL. The repository describes itself as: :hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error…

When your agent uses it

  • Asked to test a model
  • Validate a view
  • Check for nulls
  • Add data quality checks

Example prompts

  • “/authoring-data-quality-checks”

Workflow steps

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

  1. posthog:data-quality-check-create
  2. posthog:data-quality-check-run — returns a suite run
  3. Poll system.information_schema.data_quality_check_runs (or

What it can do on your machine

Read from SKILL.md and the folder at commit 10f9ad7. 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

    Shell commands in SKILL.md call:

    • dbt

    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

Authoring Data Quality Checks loads about 2.8k tokens when it runs. Until then it costs about 207 tokens; SKILL.md has 1,442 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~207
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k

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 1,442 words (~2,755 tokens).

“A check is one assertion about one warehouse table, view, or HogQL catalog metric. It compiles to a count-only HogQL query and passes when it finds zero failing rows, like dbt test. Failing rows are never stored; only counts and…”

— opening of SKILL.md by PostHog, Custom licence
name
authoring-data-quality-checks

Read the full SKILL.md on GitHub

Files

Just SKILL.md in products/data_quality/skills/authoring-data-quality-checks of PostHog/posthog.

Open the folder on GitHubat commit 10f9ad7

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders. This page covers the copy in PostHog/posthog, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Authoring Data Quality 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.

Authoring Data Quality Checks compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Authoring Data Quality Checks this skillPostHog/posthog40k—~2.8kAutomated safety check: PassCustom licence
Data Quality Checksmohitagw15856/pm-claude-skills1.4k—~919Automated safety check: PassMIT
Dbt Model Specmohitagw15856/pm-claude-skills1.4k—~939Automated safety check: PassMIT
Dbt Databricks PR Readydatabricks/dbt-databricks380—~2.8kAutomated safety check: PassApache-2.0
Data Quality Frameworkswshobson/agents40k11 repos~1.1kAutomated safety check: PassMIT
Senior Data Engineerbenchflow-ai/skillsbench1.8k—~5.9kAutomated safety check: PassMIT

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  • Data Quality Checks

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Works with

Categories

Questions about Authoring Data Quality Checks

What does Authoring Data Quality Checks do?

Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential…. Authoring Data Quality Checks is an agent skill from PostHog/posthog, published by the product's own GitHub organization. Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential integrity, row-count bounds, freshness, and custom HogQL.

When should I use Authoring Data Quality Checks?

Authoring Data Quality Checks fits situations like: asked to test a model; validate a view; check for nulls; add data quality checks.

How do I install Authoring Data Quality Checks in Claude Code?

Run `npx skills add PostHog/posthog --skill authoring-data-quality-checks -a claude-code`. Or copy the skill folder (products/data_quality/skills/authoring-data-quality-checks in PostHog/posthog) into .claude/skills/authoring-data-quality-checks in your project. Claude Code loads it when a task matches its description.

How do I install Authoring Data Quality Checks in Codex?

Run `npx skills add PostHog/posthog --skill authoring-data-quality-checks -a codex`. Or copy the skill folder (products/data_quality/skills/authoring-data-quality-checks in PostHog/posthog) into .agents/skills/authoring-data-quality-checks in your project. Codex loads it when a task matches its description.

Can I use Authoring Data Quality 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 PostHog/posthog --skill authoring-data-quality-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/authoring-data-quality-checks, .gemini/skills/authoring-data-quality-checks, .github/skills/authoring-data-quality-checks and .opencode/skills/authoring-data-quality-checks in your project.

What does Authoring Data Quality Checks need to run?

Going by SKILL.md and its folder, Authoring Data Quality Checks needs the command-line tools its instructions call (dbt).

Does Authoring Data Quality 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 Authoring Data Quality 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 Authoring Data Quality Checks use?

Authoring Data Quality 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 Authoring Data Quality Checks 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 Authoring Data Quality Checks?

Skills that share tags, products or a category with Authoring Data Quality Checks: Data Quality Checks (mohitagw15856/pm-claude-skills, 1.4k stars), Dbt Model Spec (mohitagw15856/pm-claude-skills, 1.4k stars), Dbt Databricks PR Ready (databricks/dbt-databricks, 380 stars) and Data Quality Frameworks (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Authoring Data Quality Checks?

PostHog (a GitHub organization, an official publisher) maintains it in PostHog/posthog, which has 40,182 GitHub stars. The repository holds 252 skills in this directory. The repository was last updated on October 8, 2026.

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