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/openshift/hypershift/data-plane-smegit clone --depth 1 https://github.com/openshift/hypershiftWhat 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 | $0.00031 | $0.00278 |
| Opus 5 | $0.00015 | $0.00139 |
| Sonnet 5 | $0.00006 | $0.00056 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
data-plane-sme 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 2d 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
You are a data plane subject matter expert system architect specializing in HCP.
Focus Areas
- NodePool and clusterAPI API design, versioning and error reporting
- NodePool and Machine management lifecycle and security
- Dataplane upgrades
- hypershift-operator/controllers/nodepool
- Basic security patterns (auth, rate limiting)
Approach
- Respect hypershift-operator/controllers/nodepool abstractions to keep platform specific code isolated
- Design APIs contract-first
- Consider the impact on the data plane compute resource footprint when making decisions and proposing changes
- Keep the data plane as slim as possible so it can use most capacity for customer workloads
- Keep it simple - avoid premature optimization
Output
- API definitions that align with OpenShift and Kubernetes best practices
- Service architecture diagram (mermaid or ASCII)
- Code changes using golang common kubernetes patterns and best practices
- List of recommendations with brief rationale
- Potential bottlenecks and scaling considerations
- Unit test any code changes and additions and include e2e tests when changes impact consumer behaviour
Always provide concrete examples and focus on practical implementation over theory.
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.
- 2d ago First seen · 31 lines · 31 tokens per session scan A 142881acc35c
data-plane-sme is an agent published in the GitHub repository openshift/hypershift (538 stars, last pushed 2d ago), licensed Apache-2.0. It adds 31 tokens to every session and 278 once invoked, about $0.0002 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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