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 vaquarkhan/data-engineering-agent-skills --skill mcp-data-observability-integrationgit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skillsWrote 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/vaquarkhan/data-engineering-agent-skills/mcp-data-observability-integration)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/mcp-data-observability-integration"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/mcp-data-observability-integration/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/vaquarkhan/data-engineering-agent-skills/mcp-data-observability-integration"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/mcp-data-observability-integration.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00062 | $0.00998 |
| Opus 5 | $0.00031 | $0.00499 |
| Sonnet 5 | $0.00012 | $0.00200 |
| Haiku 4.5 | $0.00006 | $0.00100 |
Grade A, and why
mcp-data-observability-integration 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 8d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Data Observability Integration
Overview
Agents that cannot see production signals guess at fixes — scaling clusters blindly, rerunning jobs that OOM for structural reasons, or changing Kafka consumers without checking lag. This skill pairs MCP server templates with safe read-only observability workflows so diagnosis precedes mutation.
When to Use
- diagnosing Spark OOM, shuffle skew, or stage failures
- inspecting Kafka consumer group lag before replay or consumer changes
- reviewing Airflow DAG run state, task duration drift, or failed retries
- validating warehouse publish state before reopening downstream consumers
- setting up IDE-integrated observability for data engineering agents
Do not use MCP write capabilities for destructive fixes during incident triage unless explicitly approved and scoped.
Workflow
-
Choose the smallest MCP surface for the question.
- Spark plans and stage metrics:
mcp/spark.mcp.jsonormcp/databricks.mcp.json - Kafka lag and topic metadata:
mcp/kafka.mcp.json - Orchestration run state:
mcp/airflow.mcp.json - Warehouse inspection:
mcp/snowflake.mcp.json,mcp/bigquery.mcp.json, ormcp/postgres.mcp.json - Release and job metadata:
mcp/dbt-cloud.mcp.json,mcp/github.mcp.json
- Spark plans and stage metrics:
-
Configure read-only first. From
mcp/README.md:- replace placeholder
commandwith the MCP server binary in use - scope credentials to read-only inspection roles
- set allowlists (
topic, catalog, schema) to minimum necessary scope - validate connectivity outside the agent session before relying on tool output
- replace placeholder
-
Establish the diagnostic sequence. Typical order:
- confirm symptom (lag, failure rate, freshness breach)
- pull live metadata (consumer lag, last successful run, stage skew)
- compare against baseline or SLA from
data-observability-and-sla-management - form hypothesis before proposing code or infra changes
- record findings in incident or backfill evidence templates when action follows
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.
- 8d ago First seen · 85 lines · 62 tokens per session scan A 8da2fbabb1f6
mcp-data-observability-integration is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 998 once invoked, about $0.0003 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 2026-09-03.
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