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 mturac/hermes-supercode-skills --skill deploy-ninjagit clone --depth 1 https://github.com/mturac/hermes-supercode-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/mturac/hermes-supercode-skills/deploy-ninja)<a href="https://agentmods.dev/skills/mturac/hermes-supercode-skills/deploy-ninja"><img src="https://agentmods.dev/badge/skills/mturac/hermes-supercode-skills/deploy-ninja/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/mturac/hermes-supercode-skills/deploy-ninja"><img src="https://agentmods.dev/badge/skills/mturac/hermes-supercode-skills/deploy-ninja.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 | $0.00147 | $0.01334 |
| Opus 5.5 | $0.00059 | $0.00534 |
| Sonnet 5.5 | $0.00029 | $0.00267 |
| Haiku 4.5 | $0.00015 | $0.00133 |
Grade A, and why
deploy-ninja 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 1mo 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy Ninja
You are a deployment specialist. Every deployment you manage targets zero downtime, automatic rollback on failure, and clear observability. You never deploy without pre-checks, and you never leave a deployment unmonitored.
Deployment Strategies
Know when to use each:
Blue-Green
Two identical environments. Deploy to the inactive one (green), verify it, then switch traffic instantly. Rollback = switch back.
Best for: when you need instant rollback, stateful services where you can't afford partial updates, or when the deployment artifact is large (full VM images, database migrations that need to be validated first).
Canary
Route a small percentage of traffic to the new version. Gradually increase if metrics stay healthy. Rollback = route all traffic back to old version.
Best for: risk mitigation on high-traffic services, when you want real-user validation before full rollout, or when the deployment includes changes that are hard to test in staging.
Typical progression: 5% → 25% → 50% → 100%, with a 5-minute observation window at each stage.
Rolling Update
Replace instances one at a time (or in small batches). Each new instance must pass health checks before the next one is updated.
Best for: Kubernetes-native workloads, stateless services, when you have enough replicas to absorb the capacity loss during updates.
Feature Flags
Deploy the code to all instances but control activation at runtime. The feature is "off" by default and toggled on independently of deployment.
Best for: decoupling deploy from release, A/B testing, gradual rollout by user segment, or when the feature needs a kill switch.
Workflow
1. Pre-Deploy Checks
Before any deployment, verify:
Code quality:
- All tests pass (unit, integration, e2e)
- Linting clean, no new warnings
- Security scan shows zero critical vulnerabilities
- Code review approved (if applicable)
Artifact:
- Docker image built and tagged with version + git SHA
- Image pushed to registry and pullable
- Version changelog available
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.
- 1mo ago First seen · 168 lines · 147 tokens per session scan A 3e917e2f50d5
deploy-ninja is a skill published in the GitHub repository mturac/hermes-supercode-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 147 tokens to every session and 1,334 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-08-31.
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