Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add astronomer/agents --skill cosmos-dbt-coregit clone --depth 1 https://github.com/astronomer/agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/astronomer/agents/cosmos-dbt-core)<a href="https://agentmods.dev/skills/astronomer/agents/cosmos-dbt-core"><img src="https://agentmods.dev/badge/skills/astronomer/agents/cosmos-dbt-core/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/astronomer/agents/cosmos-dbt-core"><img src="https://agentmods.dev/badge/skills/astronomer/agents/cosmos-dbt-core.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.03644 |
| Opus 5 | $0.00036 | $0.01822 |
| Sonnet 5 | $0.00015 | $0.00729 |
| Haiku 4.5 | $0.00007 | $0.00364 |
Grade A, and why
cosmos-dbt-core scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cosmos + dbt Core: Implementation Checklist
Execute steps in order. Prefer the simplest configuration that meets the user's constraints.
Version note: This skill targets Cosmos 1.11+ and Airflow 3.x. If the user is on Airflow 2.x, adjust imports accordingly (see Appendix A).
Reference: Latest stable: https://pypi.org/project/astronomer-cosmos/
Before starting, confirm: (1) dbt engine = Core (not Fusion → use cosmos-dbt-fusion), (2) warehouse type, (3) Airflow version, (4) execution environment (Airflow env / venv / container), (5) DbtDag vs DbtTaskGroup vs individual operators, (6) manifest availability.
1. Configure Project (ProjectConfig)
| Approach | When to use | Required param |
|---|---|---|
| Project path | Files available locally | dbt_project_path |
| Manifest only | dbt_manifest load |
manifest_path + project_name |
from cosmos import ProjectConfig
_project_config = ProjectConfig(
dbt_project_path="/path/to/dbt/project",
# manifest_path="/path/to/manifest.json", # for dbt_manifest load mode
# project_name="my_project", # if using manifest_path without dbt_project_path
# install_dbt_deps=False, # if deps precomputed in CI
)
2. Choose Parsing Strategy (RenderConfig)
Pick ONE load mode based on constraints:
| Load mode | When to use | Required inputs | Constraints |
|---|---|---|---|
dbt_manifest |
Large projects; containerized execution; fastest | ProjectConfig.manifest_path |
Remote manifest needs manifest_conn_id |
dbt_ls |
Complex selectors; need dbt-native selection | dbt installed OR dbt_executable_path |
Can also be used with containerized execution |
dbt_ls_file |
dbt_ls selection without running dbt_ls every parse | RenderConfig.dbt_ls_path |
select/exclude won't work |
automatic (default) |
Simple setups; let Cosmos pick | (none) | Falls back: manifest → dbt_ls → custom |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 457 lines · 73 tokens per session scan A 0a7311b858b0
cosmos-dbt-core is a skill published in the GitHub repository astronomer/agents (439 stars, last pushed 3d ago), licensed Apache-2.0. It adds 73 tokens to every session and 3,644 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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