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 Xiaowen-Jiang/agent-enterprise --skill deployment_planninggit clone --depth 1 https://github.com/Xiaowen-Jiang/agent-enterpriseWrote 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/xiaowen-jiang/agent-enterprise/deployment_planning)<a href="https://agentmods.dev/skills/xiaowen-jiang/agent-enterprise/deployment_planning"><img src="https://agentmods.dev/badge/skills/xiaowen-jiang/agent-enterprise/deployment_planning.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 5.1 | $0.00015 | $0.00465 |
| Opus 5 | $0.00008 | $0.00233 |
| Sonnet 5 | $0.00003 | $0.00093 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
Deployment Planning 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.
What it actually says
Process
- Pre-deployment checklist:
- All tests passing
- Code reviewed and approved
- Database migrations tested
- Environment variables configured
- Dependencies up to date
- Deployment strategy — Choose approach:
- Rolling update: Gradual replacement, zero-downtime
- Blue-green: Switch traffic between two environments
- Canary: Route small percentage of traffic to new version
- Big bang: Replace all at once (simplest, riskiest)
- Rollback plan — How to revert if something goes wrong
- Health checks — What endpoints/metrics confirm the deployment is healthy
- Monitoring — What to watch during and after deployment
- Communication — Who needs to know, when to notify
Output Format
## Deployment Runbook: [Release Name/Version]
### Pre-Deployment
- [ ] Tests passing on CI
- [ ] Database migration tested on staging
- [ ] Environment variables verified
- [ ] Rollback procedure documented
### Deployment Steps
1. [Step-by-step deployment procedure]
### Health Verification
- [ ] Health endpoint returns 200: GET /health
- [ ] Key metric within normal range: [metric name]
- [ ] No error spike in logs (check for 5 minutes)
### Rollback Procedure
1. [Step-by-step rollback if deployment fails]
### Post-Deployment
- [ ] Monitor error rates for 30 minutes
- [ ] Verify key user flows
- [ ] Update status page / notify team
Guidelines
- Always have a rollback plan before deploying
- Test migrations on a copy of production data first
- Deploy during low-traffic periods when possible
- Monitor error rates closely for 30 minutes after deployment
- Keep deployments small — smaller changes are easier to debug
- Document everything — the next person to deploy should be able to follow your runbook
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 · 64 lines · 15 tokens per session scan A d0432a760381
Deployment Planning is a skill published in the GitHub repository Xiaowen-Jiang/agent-enterprise (52 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 465 once invoked, about $0.0001 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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