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 omnigentx/jarvis --skill dso-workflowgit clone --depth 1 https://github.com/omnigentx/jarvisWrote 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/omnigentx/jarvis/dso-workflow)<a href="https://agentmods.dev/skills/omnigentx/jarvis/dso-workflow"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/dso-workflow/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/omnigentx/jarvis/dso-workflow"><img src="https://agentmods.dev/badge/skills/omnigentx/jarvis/dso-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 53 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00036 | $0.00543 |
| Opus 5.5 | $0.00014 | $0.00217 |
| Sonnet 5.5 | $0.00007 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
dso-workflow 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DSO Workflow
Your Process
- Security review → OWASP Top 10, dependency scan, secrets check
- CI/CD pipeline → GitHub Actions setup and validation
- Docker management → Build, configure, optimize containers
- Deployment → Staging → approval → production
- Monitoring → Health checks, log analysis
Security Review Checklist
- No hardcoded secrets in code
- Dependencies scanned for vulnerabilities
- Input validation on all endpoints
- Authentication/authorization properly implemented
- Docker images use minimal base images
- CORS properly configured
CI/CD Pipeline Stages
Push → Lint → Test → Build → Deploy (staging) → Approval → Deploy (prod)
For pipelines with branching (security gate, manual approval, multi-env)
include a Mermaid flowchart so reviewers see the gates clearly:
flowchart LR
Push --> Lint
Lint --> Test
Test --> SecScan{Sec scan}
SecScan -- pass --> Build
SecScan -- fail --> Block[Block + alert]
Build --> Staging[Deploy staging]
Staging --> Approve{Manual approval}
Approve -- yes --> Prod[Deploy prod]
Approve -- no --> Hold[Hold]
Rules:
- ❌ DO NOT hardcode secrets in source → use GitHub Secrets.
- ✅ Scan dependencies for vulnerabilities.
- ✅ Scan Docker images before deploying.
- Staging: auto-deploy on
develop. - Production: manual approval required.
- Rollback: keep 3 previous versions.
Deliverables
| Output | Format |
|---|---|
| Security review report | SECURITY_REVIEW.md |
| CI/CD pipeline config | .github/workflows/ci.yml |
| Deployment runbook | DEPLOYMENT.md |
References
| Topic | File |
|---|---|
| Code review protocol | CODE_REVIEW.md |
| Git branching & conventions | GIT_WORKFLOW.md |
| Terminal execution | TERMINAL.md |
| Meeting protocol | MEETING_PROTOCOL.md |
What ships with it
4 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.
- 1mo ago First seen · 73 lines · 36 tokens per session scan A b9d030ffb8a0
dso-workflow is a skill published in the GitHub repository omnigentx/jarvis (39 stars, last pushed 4d ago), licensed MIT. It adds 36 tokens to every session and 543 once invoked, about $0.0001 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 2026-08-30.
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