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 jnPiyush/AgentX --skill genaiopsgit clone --depth 1 https://github.com/jnPiyush/AgentXWrote 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/jnpiyush/agentx/genaiops)<a href="https://agentmods.dev/skills/jnpiyush/agentx/genaiops"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/genaiops/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/jnpiyush/agentx/genaiops"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/genaiops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.01230 |
| Opus 5.5 | $0.00018 | $0.00492 |
| Sonnet 5.5 | $0.00009 | $0.00246 |
| Haiku 4.5 | $0.00005 | $0.00123 |
Grade A, and why
genaiops 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GenAIOps
WHEN: Designing or operating production GenAI systems with release gates, prompt/model versioning, evaluation automation, observability, drift monitoring, rollback, and governance.
When to Use
- Defining how prompts, models, and tools move from dev to production
- Setting blocking evaluation gates before promotion
- Designing LLM observability, tracing, and runtime dashboards
- Managing prompt/model rollout, canarying, rollback, and baseline updates
- Coordinating feedback loops, drift detection, and issue remediation
Decision Tree
Operating GenAI in production?
+- Need pre-release quality control?
| - Add evaluation gates and acceptance baselines
+- Need runtime visibility?
| - Add tracing, cost, latency, and failure dashboards
+- Need safe rollout?
| - Use canary/pilot plus rollback path
+- Need prompt and model governance?
| - Track versions, approvals, and baseline deltas together
+- Need continuous quality improvement?
| - Add drift monitoring and feedback loops
-- Need compliance or incident readiness?
- Add audit trails, ownership, escalation, and change records
Core Rules
- Treat prompts, models, tools, eval datasets, and rubrics as release-managed artifacts.
- No production promotion without baseline comparison and explicit pass/fail thresholds.
- Trace every important agent run with enough metadata to explain regressions, cost spikes, and tool failures.
- Rollout must include rollback: every prompt/model promotion needs a last-known-good fallback.
- Drift detection is not optional for long-lived agents; monitor quality, not only uptime.
Operating Model
Prompt / Model Change
-> local validation
-> regression dataset run
-> baseline comparison
-> reviewer approval
-> canary or pilot rollout
-> runtime monitoring
-> baseline promotion or rollback
Required Artifact Families
- prompts and templates
- evaluation datasets and rubrics
- accepted baseline files
- release decision records
- tracing and telemetry configuration
- rollback instructions and fallback versions
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 Changed f30403baeace
- 1mo ago First seen · 138 lines · 45 tokens per session scan A bc5a35ea902b
genaiops is a skill published in the GitHub repository jnPiyush/AgentX (16 stars, last pushed 3d ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,230 once invoked, about $0.0002 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 2026-09-03.
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