huawei-sdrs-dr-drill

huawei-sdrs-dr-drill is a skill for Claude Code, Codex from binrogithub/1-3-Cloud-Adoption-Skills. It costs 49 tokens per session (3,678 once invoked), scanned A, original, no licence file.

A supervised disaster-recovery drill for Huawei Cloud SDRS. A disaster-recovery drill is a controlled test of whether replicated systems can be recovered without affecting production.

In plain words
What is it for?
Use it to define an isolated drill, recover selected resources for testing, check the results, measure RPO and RTO, and produce a report.
Why use it?
It provides a structured way to test replication readiness and recovery results before a real outage. It also records RPO, how much recent data could be lost, and RTO, how long recovery takes.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to define an isolated drill, recover selected resources for testing, check the results, measure RPO and RTO, and produce a report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill
Install

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.

Any agent
npx skills add binrogithub/1-3-Cloud-Adoption-Skills --skill huawei-sdrs-dr-drill
Clone the repo
git clone --depth 1 https://github.com/binrogithub/1-3-Cloud-Adoption-Skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for huawei-sdrs-dr-drill

README.md
[![agentmods](https://agentmods.dev/badge/skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill/github.svg)](https://agentmods.dev/skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill)
Your own site
<a href="https://agentmods.dev/skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill"><img src="https://agentmods.dev/badge/skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill/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.

agentmods 80×15 button for huawei-sdrs-dr-drill

Your own site · 80×15
<a href="https://agentmods.dev/skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill"><img src="https://agentmods.dev/badge/skills/binrogithub/1-3-cloud-adoption-skills/huawei-sdrs-dr-drill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,678 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.03678
Opus 5 $0.00024 $0.01839
Sonnet 5 $0.00010 $0.00736
Haiku 4.5 $0.00005 $0.00368

Measured 10d ago against content hash 734ea667c491, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

huawei-sdrs-dr-drill 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 10d ago.

The scan reads SKILL.md. This mod also ships 24 executable files (shared-mcps/huaweicloud-pricing/src/find_ebs_usage_types.py, shared-mcps/huaweicloud-pricing/src/huawei-signer.mjs, shared-mcps/huaweicloud-pricing/src/pricing_api_helper.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

AI-Assist-Migration/Cloud-Foundation/DR-and-Backup/sdrs-cross-region-dr/huawei-sdrs-dr-drill/SKILL.md · 465 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 10d ago First seen · 465 lines · 49 tokens per session scan A 734ea667c491

Subscribe to this mod's changes

huawei-sdrs-dr-drill is a skill published in the GitHub repository binrogithub/1-3-Cloud-Adoption-Skills (11 stars, last pushed 3d ago), with no licence file. It adds 49 tokens to every session and 3,678 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 2026-08-30.