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 agentmods add skills/astronomer/agents/blueprintnpx skills add astronomer/agents --skill blueprintgit 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/blueprint)<a href="https://agentmods.dev/skills/astronomer/agents/blueprint"><img src="https://agentmods.dev/badge/skills/astronomer/agents/blueprint.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00049 | $0.06311 |
| Opus 5 | $0.00024 | $0.03155 |
| Sonnet 5 | $0.00010 | $0.01262 |
| Haiku 4.5 | $0.00005 | $0.00631 |
Grade A, and why
blueprint scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST /api/v2/dags/customer_pipeline/dagRuns \ How it starts
The opening of the file, as written. The whole thing — 721 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blueprint Implementation
You are helping a user work with Blueprint, a system for composing Airflow DAGs from YAML using reusable Python templates. Execute steps in order and prefer the simplest configuration that meets the user's needs.
Package:
airflow-blueprinton PyPI Repo: https://github.com/astronomer/blueprint Requires: Python 3.10+, Airflow 2.5+, Blueprint 0.3.0+
Before Starting
Confirm with the user:
- Airflow version ≥2.5
- Python version ≥3.10
- Use case: Blueprint is for standardized, validated templates. If user needs full Airflow flexibility, suggest writing DAGs directly or using DAG Factory instead.
Determine What the User Needs
| User Request | Action |
|---|---|
| "Create a blueprint" / "Define a template" | Go to Creating Blueprints |
| "Build a template from other templates" | Go to Composing Templates |
| "Create a DAG from YAML" / "Compose steps" | Go to Composing DAGs in YAML |
| "Use a blueprint in an existing Python DAG" / "Generate DAGs in a loop" | Go to Blueprints in Python DAGs |
| "Customize DAG args" / "Add tags to DAG" | Go to Customizing DAG-Level Configuration |
| "Override config at runtime" / "Trigger with params" | Go to Runtime Parameter Overrides |
| "Post-process DAGs" / "Add callback" | Go to Post-Build Callbacks |
| "Validate my YAML" / "Lint blueprint" | Go to Validation Commands |
| "Set up blueprint in my project" | Go to Project Setup |
| "Version my blueprint" | Go to Versioning |
| "Generate schema" / "Astro IDE setup" | Go to Schema Generation |
| Blueprint errors / troubleshooting | Go to Troubleshooting |
Project Setup
If the user is starting fresh, guide them through setup:
1. Install the Package
# Add to requirements.txt
airflow-blueprint>=0.3.0
# Or install directly
pip install airflow-blueprint
2. Create the Loader
Create dags/loader.py:
from blueprint import build_all_dags
build_all_dags()
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.
- 4d ago First seen · 721 lines · 49 tokens per session scan A 4e38d05652d6
blueprint is a skill published in the GitHub repository astronomer/agents (432 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 6,311 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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