pointblank
posit-dev/pointblank
This skill guides the definition and enforcement of data contracts and pipeline validation using the Pointblank library. It covers creating schemas, validation steps, and orchestrating input/output checks.
479 30MITUpdated 2026-08-11
84
GreatOverview
The pointblank skill facilitates robust data quality management by enabling users to define explicit structural and semantic expectations at data pipeline boundaries. It outlines how to construct Contracts, Schemas, and Validation Steps, bundle them into execution Pipelines, handle violations through warnings or exceptions, and serialize definitions to YAML for version control.
Capabilities
- ▸Define structural schemas and column expectations
- ▸Create reusable semantic validation steps
- ▸Orchestrate source and target validation within pipelines
- ▸Serialize and deserialize contracts to/from YAML and dictionaries
- ▸Configure violation responses such as raising exceptions, logging, or warning
Best for
Setting up source and target data contracts for ingestion pipelines, Validating table schemas and column values before and after transformations, Serializing and deserializing data contracts using YAML formats, Handling pipeline violations via logging, warnings, or halting execution
Works with
Claude CodeCodexChatGPTGemini CLICursorGitHub CopilotOpenCode
Evoa Score breakdown= Σ (score × weight)
84Task usefulness20%88 → +17.6
実タスクにどれだけ役立つか（機能の豊富さ・用途の明確さ）。 — AIによるcapabilities/use-cases解析
Code quality15%90 → +13.5
実装・指示の品質。 — AIによるSKILL.md/README解析
Maintenance15%100 → +15.0
リポジトリがどれだけ活発に保守されているか。 — GitHub 最終push日時の新しさ
Documentation12%37 → +4.4
ドキュメントの充実度・分かりやすさ。 — README/独自要約の情報量
Security15%100 → +15.0
危険・不審な挙動が無いか。 — AIによるセキュリティレビュー
Originality10%75 → +7.5
ありふれたラッパーではない独自性。 — AIによる独自性判定
Popularity8%68 → +5.4
コミュニティの採用度。 — GitHub Stars/Forks（対数スケール）
Compatibility5%100 → +5.0
対応AIエージェントの広さ。 — AIによる対応エージェント判定
Weighted total83.5 / 100
ライセンス不明/制限あり（Red）のSkillは総合スコアに0.85倍の補正を適用します。 ランキングはこのScoreのみで決まり、広告で変わりません。 算出方法の詳細 →
Security considerations
This skill processes data validation rules and interacts with tabular datasets. Ensure that sensitive dataset contents or credentials are not hardcoded into contract YAML or python files.
Categories
Summary and analysis are original content generated by AI Skills Rank. The skill's source text is not reproduced here — view it on the linked repository.