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/anomalyarmor/agents/lineagenpx skills add anomalyarmor/agents --skill lineagegit clone --depth 1 https://github.com/anomalyarmor/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/anomalyarmor/agents/lineage)<a href="https://agentmods.dev/skills/anomalyarmor/agents/lineage"><img src="https://agentmods.dev/badge/skills/anomalyarmor/agents/lineage.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 | $0.00040 | $0.01063 |
| Opus 5 | $0.00020 | $0.00531 |
| Sonnet 5 | $0.00008 | $0.00213 |
| Haiku 4.5 | $0.00004 | $0.00106 |
Grade A, and why
armor-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 3d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Lineage
Explore upstream dependencies and downstream consumers of your data assets.
Prerequisites
- AnomalyArmor API key configured (
~/.armor/config.yamlorARMOR_API_KEYenv var) - Python SDK installed (
pip install anomalyarmor)
When to Use
- "What depends on this table?"
- "Where does this data come from?"
- "Impact analysis for changes"
- "Show upstream dependencies"
- "List downstream consumers"
- "Trace data flow"
Concepts
Directions
- upstream: Tables that this table depends on (data sources)
- downstream: Tables that depend on this table (data consumers)
- both: Full lineage graph in both directions
Depth
- depth=1: Direct dependencies only
- depth=2: Two levels of dependencies
- depth=3+: Extended dependency chain (max 5)
Steps
- Identify the asset to analyze
- Determine direction (upstream, downstream, or both)
- Choose appropriate depth (start with 1-2)
- Call
client.lineage.get()to fetch lineage graph - Analyze the graph for impact or root cause
Example Usage
Find Upstream Dependencies
from anomalyarmor import Client
client = Client()
# Get upstream lineage (where data comes from)
lineage = client.lineage.get(
asset_id="asset-uuid",
direction="upstream",
depth=2
)
print(f"Table: {lineage.root.qualified_name}")
print(f"\nUpstream Dependencies ({len(lineage.upstream)} tables):")
for node in lineage.upstream:
print(f" {node.qualified_name}")
if node.asset_type:
print(f" Type: {node.asset_type}")
Find Downstream Consumers
# Get downstream lineage (what depends on this)
lineage = client.lineage.get(
asset_id="asset-uuid",
direction="downstream",
depth=2
)
print(f"Table: {lineage.root.qualified_name}")
print(f"\nDownstream Consumers ({len(lineage.downstream)} tables):")
for node in lineage.downstream:
print(f" {node.qualified_name}")
Impact Analysis
# Full impact analysis before making changes
lineage = client.lineage.get(
asset_id="asset-uuid",
direction="both",
depth=3
)
print("=== IMPACT ANALYSIS ===")
print(f"\nTable: {lineage.root.qualified_name}")
# Upstream (what feeds this table)
print(f"\nData Sources ({len(lineage.upstream)} tables):")
for node in lineage.upstream:
print(f" <- {node.qualified_name}")
# Downstream (what will be affected by changes)
print(f"\nWill Impact ({len(lineage.downstream)} tables):")
for node in lineage.downstream:
print(f" -> {node.qualified_name}")
# Edges show the relationships
print(f"\nRelationships ({len(lineage.edges)} edges):")
for edge in lineage.edges:
print(f" {edge.source} -> {edge.target}")
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.
- 3d ago First seen · 166 lines · 40 tokens per session scan A 7f0b655eed38
armor-lineage is a skill published in the GitHub repository anomalyarmor/agents (1 stars, last pushed 3mo ago), licensed MIT. It adds 40 tokens to every session and 1,063 once invoked, about $0.0002 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 2026-08-31.
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
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