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 The-AI-Directory-Company/agents-and-skills --skill disaster-recovery-plangit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-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/the-ai-directory-company/agents-and-skills/disaster-recovery-plan)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/disaster-recovery-plan"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/disaster-recovery-plan/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/the-ai-directory-company/agents-and-skills/disaster-recovery-plan"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/disaster-recovery-plan.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 | $0.00035 | $0.01694 |
| Opus 5 | $0.00017 | $0.00847 |
| Sonnet 5 | $0.00007 | $0.00339 |
| Haiku 4.5 | $0.00003 | $0.00169 |
Grade A, and why
disaster-recovery-plan 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Disaster Recovery Plan
Before you start
Gather the following from the user before writing:
- What systems does this plan cover? (Service names, data stores, and their business functions)
- What are the business-critical operations? (Revenue-generating flows, regulatory obligations, customer-facing services)
- What is the acceptable data loss? (RPO — Recovery Point Objective: can you lose 0 seconds, 5 minutes, 1 hour, or 24 hours of data?)
- What is the acceptable downtime? (RTO — Recovery Time Objective: how long can the system be unavailable before business impact is severe?)
- What disaster scenarios must be covered? (Region outage, database corruption, ransomware, vendor failure, physical site loss)
If the user says "write a DR plan for our app," push back: "Which failure scenario? A database corruption recovery is a different plan from a full region failover. Each scenario gets its own procedure with its own RPO/RTO targets."
Disaster recovery plan template
1. Scope and objectives
State what this plan covers and what it does not. Define the specific systems, environments, and failure scenarios in scope. List any systems explicitly excluded and reference their separate DR plans if they exist.
Define recovery objectives for each system:
| System | RPO | RTO | Tier | Justification |
|---|---|---|---|---|
| Payment processing | 0 (zero data loss) | 15 minutes | Tier 1 | Revenue-critical, regulatory requirement |
| User database | 5 minutes | 30 minutes | Tier 1 | All services depend on auth |
| Analytics pipeline | 24 hours | 4 hours | Tier 2 | No revenue impact, can reprocess |
| Internal wiki | 24 hours | 48 hours | Tier 3 | Low urgency, daily backups sufficient |
Tier definitions:
- Tier 1: Restore first. Business stops without this system.
- Tier 2: Restore after Tier 1. Degraded operations are tolerable short-term.
- Tier 3: Restore last. No immediate business impact.
2. Backup strategy
For each system, document:
What ships with it
3 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.
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 · 131 lines · 35 tokens per session scan A fe9fff75ee27
disaster-recovery-plan is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 1,694 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 2026-09-03.
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