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 data-platform-disaster-recovery-and-business-continuitygit 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/data-platform-disaster-recovery-and-business-continuity)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/data-platform-disaster-recovery-and-business-continuity"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/data-platform-disaster-recovery-and-business-continuity/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/data-platform-disaster-recovery-and-business-continuity"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/data-platform-disaster-recovery-and-business-continuity.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 | $0.00065 | $0.00693 |
| Opus 5 | $0.00032 | $0.00347 |
| Sonnet 5 | $0.00013 | $0.00139 |
| Haiku 4.5 | $0.00006 | $0.00069 |
Grade A, and why
data-platform-disaster-recovery-and-business-continuity 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 12d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Platform Disaster Recovery And Business Continuity
Overview
Use this skill when the question is how the data platform survives major failure, not only how one incident is handled. It helps agents design recovery objectives, backup and restore paths, control-plane recovery, failover decisions, and repeatable restore drills for data systems.
When to Use
- defining
RTOandRPOfor critical datasets or platform services - planning region, account, or environment failover
- validating backup and restore behavior for warehouses, lakes, or stateful processors
- designing business continuity for shared data products and critical publish paths
- running recovery drills before a real outage forces them
Do not confuse incident handling with disaster recovery planning. Disaster recovery is the plan for major platform loss or sustained unavailability.
Workflow
-
Classify the critical services and data products. Identify:
- critical datasets
- control-plane dependencies
- orchestration and metadata services
- downstream consumer and business impact
-
Define recovery objectives. Include:
RTORPO- acceptable degraded mode
- mandatory publish protections during failover
-
Map recovery assets and dependencies. Cover:
- backups and snapshots
- checkpoint or incremental state
- orchestration definitions
- secrets and access paths
- lineage and metadata services
- validation and reconciliation controls after restore
-
Choose the recovery strategy. Options may include:
- restore in place
- warm standby
- cold standby
- cross-region or cross-account failover
- consumer-facing degraded mode with blocked publish
-
Prove the recovery path. Run drills for:
- restore time
- checkpoint continuity
- publish blocking and reopen criteria
- reconciliation after restore
- ownership and escalation behavior
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "The cloud provider already handles availability." | Provider uptime does not replace dataset restore, metadata recovery, or publish-safe failover design. |
| "We have backups, so we are covered." | Untested backups and undefined restore ownership do not prove business continuity. |
| "We can work out the failover steps during an outage." | Major outages are the worst time to discover recovery dependencies or missing permissions. |
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.
- 12d ago First seen · 86 lines · 65 tokens per session scan A 67a1de5cd07f
data-platform-disaster-recovery-and-business-continuity is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 65 tokens to every session and 693 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 2026-08-30.
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