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 annotating-task-lineagegit 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/annotating-task-lineage)<a href="https://agentmods.dev/skills/astronomer/agents/annotating-task-lineage"><img src="https://agentmods.dev/badge/skills/astronomer/agents/annotating-task-lineage/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/annotating-task-lineage"><img src="https://agentmods.dev/badge/skills/astronomer/agents/annotating-task-lineage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 264 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00051 | $0.02561 |
| Opus 5.5 | $0.00020 | $0.01024 |
| Sonnet 5.5 | $0.00010 | $0.00512 |
| Haiku 4.5 | $0.00005 | $0.00256 |
Grade A, and why
annotating-task-lineage 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- annotating-task-lineage — 100% identical, 1 lines differ
How it starts
The opening of the file, as written. The whole thing — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Annotating Task Lineage with Inlets & Outlets
This skill guides you through adding manual lineage annotations to Airflow tasks using inlets and outlets.
Reference: See the OpenLineage provider developer guide for the latest supported operators and patterns.
On Astro
Lineage annotations defined with inlets and outlets are visualized in Astro's enhanced Lineage tab, which provides cross-DAG and cross-deployment lineage views. This means your annotations are immediately visible in the Astro UI, giving you a unified view of data flow across your entire Astro organization.
When to Use This Approach
| Scenario | Use Inlets/Outlets? |
|---|---|
Operator has OpenLineage methods (get_openlineage_facets_on_*) |
❌ Modify the OL method directly |
| Operator has no built-in OpenLineage extractor | ✅ Yes |
| Simple table-level lineage is sufficient | ✅ Yes |
| Quick lineage setup without custom code | ✅ Yes |
| Need column-level lineage | ❌ Use OpenLineage methods or custom extractor |
| Complex extraction logic needed | ❌ Use OpenLineage methods or custom extractor |
Note: Inlets/outlets are the lowest-priority fallback. If an OpenLineage extractor or method exists for the operator, it takes precedence. Use this approach for operators without extractors.
Supported Types for Inlets/Outlets
You can use OpenLineage Dataset objects or Airflow Assets for inlets and outlets:
OpenLineage Datasets (Recommended)
from openlineage.client.event_v2 import Dataset
# Database tables
source_table = Dataset(
namespace="postgres://mydb:5432",
name="public.orders",
)
target_table = Dataset(
namespace="snowflake://account.snowflakecomputing.com",
name="staging.orders_clean",
)
# Files
input_file = Dataset(
namespace="s3://my-bucket",
name="raw/events/2024-01-01.json",
)
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.
- 1mo ago First seen · 352 lines · 51 tokens per session scan A ff51650a384b
annotating-task-lineage is a skill published in the GitHub repository astronomer/agents (454 stars, last pushed 9d ago), licensed Apache-2.0. It adds 51 tokens to every session and 2,561 once invoked, about $0.0002 per session on Opus 5.5. 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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