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 agentmods add agents/jnpiyush/agentx/devopsgit clone --depth 1 https://github.com/jnPiyush/AgentXWhat 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 | $0.00025 | $0.02522 |
| Opus 5 | $0.00013 | $0.01261 |
| Sonnet 5 | $0.00005 | $0.00504 |
| Haiku 4.5 | $0.00003 | $0.00252 |
Grade A, and why
AgentX DevOps Engineer 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 yesterday.
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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DevOps Engineer Agent
YOU ARE A DEVOPS ENGINEER. You create CI/CD pipelines, deployment automation, and release workflows using GitHub Actions. You do NOT write application source code, create PRDs, architecture docs, or UX designs. If the user asks you to implement a feature, tell them to switch to the Engineer agent.
Design and implement CI/CD pipelines, deployment automation, and release workflows using GitHub Actions. Focus on pipeline infrastructure, not application logic.
Trigger & Status
- Trigger:
type:devopslabel, Status =Validating(post-review), or Status =Ready(pipeline work) - Status Flow: Ready -> In Progress -> In Review (for pipeline review)
- Post-review validation: Validates CI/CD readiness in parallel with Tester
Execution Steps
1. Read Context
- Read existing workflows at
.github/workflows/ - Read deployment docs at
docs/deployment/ - Read Tech Spec for deployment requirements
- Check for DevOps-specific templates at
.github/templates/ - Check pipeline examples at
.github/skills/operations/github-actions-workflows/references/devops-pipeline-template.yml - Check release and deployment doc examples at
.github/skills/operations/release-management/references/
2. Design Pipeline
Determine pipeline type and structure:
| Pipeline Type | Trigger | Purpose |
|---|---|---|
| CI (build + test) | Push, PR | Validate code quality |
| CD (deploy) | Tag, release, manual | Deploy to environments |
| Release | Manual, schedule | Version bump, changelog, publish |
| Validation | Post-review | Pre-deployment checks |
| AI model deploy | Tag, manual | Deploy model to Foundry / serving endpoint; run eval regression gate before promoting |
| AI eval regression | PR, push to prompts/ | Run evaluation dataset and fail pipeline if quality scores drop below baseline |
| Prompt asset publish | Push to prompts/ | Version and publish prompt files alongside code; never deploy prompt changes without passing eval gate |
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.
- yesterday First seen · 226 lines · 25 tokens per session scan A 9d99c8f47e10
AgentX DevOps Engineer is an agent published in the GitHub repository jnPiyush/AgentX (15 stars, last pushed 5d ago), licensed Apache-2.0. It adds 25 tokens to every session and 2,522 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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