dbt-artifacts-status

Assess readiness of local dbt artifacts from manifest.json and run_results.json.

Updated Dec 29, 2025

Search Tags:#readiness #manifest.json #artifact-check #run_results.json #dbt-tools #workflow-gating

Ready to run

npx skills add https://github.com/yu-iskw/dbt-artifacts-parser-ts --skill dbt-artifacts-status

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dbt-artifacts-status
Source: https://github.com/yu-iskw/dbt-artifacts-parser-ts/tree/main/plugins/dbt-tools-cli/skills/dbt-artifacts-status
Command: npx skills add https://github.com/yu-iskw/dbt-artifacts-parser-ts --skill dbt-artifacts-status

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Gate keeps downstream dbt analyses safe by verifying the presence and readiness of essential artifacts (manifest.json and run_results.json) in the target directory, reducing surprises from missing data or incomplete runs.

Core Features & Use Cases

Artifact readiness evaluation for manifest.json and run_results.json (with optional catalog.json and sources.json) to gate commands like summary, graph, and run-report.
Range of use cases including new workspace setup, CI pipelines, and recovery from artifact-related errors by providing clear readiness states.
Scenario: in a new project, confirm artifacts exist before running dbt-tools analyses to avoid failures.

Quick Start

Run the gating check and confirm artifact readiness before proceeding.

Frequently Asked Questions about dbt-artifacts-status

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I check if dbt artifacts are ready before running analyses?▼

Check dbt artifact readiness by inspecting manifest.json and run_results.json in your resolved target directory. This gating step verifies essential files exist and prevents downstream dbt-tools commands from failing due to missing data or incomplete runs.

What dbt files are required to gate downstream analysis workflows?▼

Gating dbt workflows requires manifest.json and run_results.json in the target directory. Optionally, catalog.json and sources.json can be inspected to provide a more comprehensive readiness state before running graph, summary, or run-report commands.

How do I prevent dbt-tools failures in CI pipelines from missing artifacts?▼

Prevent dbt-tools failures in CI by adding an artifact readiness check before executing analyses. Evaluating manifest.json and run_results.json ensures incomplete runs or missing data do not cause unexpected errors during automated pipeline execution.

Does the dbt artifact check require a specific target directory?▼

Yes, the dbt artifact check requires a valid --dbt-target directory or an equivalent environment configuration. It resolves this path to locate manifest.json and run_results.json, emitting structured outputs like target_dir to guide downstream steps.

What readiness states are emitted after checking dbt manifest and run results?▼

The check emits a structured readiness state including manifest.path, run_results.path, and target_dir. These outputs guide downstream dbt-tools commands by confirming artifact presence and providing clear paths for recovery from missing file errors.

Can I use artifact gating for new dbt workspace setup?▼

Yes, you can use artifact gating for new dbt workspace setup. Confirming that manifest.json and run_results.json exist before running dbt-tools analyses avoids initial failures, making it highly applicable for safely onboarding new project environments.