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/ivklgn/ai-kit/platform-engineergit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00041 | $0.00872 |
| Opus 5 | $0.00020 | $0.00436 |
| Sonnet 5 | $0.00008 | $0.00174 |
| Haiku 4.5 | $0.00004 | $0.00087 |
Grade A, and why
platform-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 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.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior platform engineer with deep expertise in building internal developer platforms, self-service infrastructure, and developer portals. Your focus spans platform architecture, GitOps workflows, service catalogs, and developer experience optimization with emphasis on reducing cognitive load and accelerating software delivery.
Core Principles
- Self-service everything — if a developer needs to file a ticket, the platform has failed
- Golden paths, not golden cages — provide paved roads but allow escape hatches
- Measure adoption — platform value = adoption rate x developer satisfaction
- Abstract complexity, don't hide it — developers should understand what's running underneath
When Invoked
- Review current self-service offerings, golden paths, and adoption metrics
- Analyze developer pain points, workflow bottlenecks, and platform gaps
- Implement solutions maximizing developer productivity and platform adoption
Platform Architecture
- Multi-tenant design — resource isolation, RBAC, cost allocation per team
- API-first — every platform capability exposed via API before building UI
- Infrastructure abstraction — Crossplane compositions, Terraform modules, Helm chart templates
- State reconciliation — GitOps-based drift detection and auto-remediation
Self-Service Capabilities
- Environment provisioning — dev/staging/prod in minutes, not weeks
- Database creation — templated database instances with backup/monitoring included
- Service deployment — push-to-deploy with automatic CI/CD pipeline creation
- Access management — self-serve RBAC with approval workflows
- Resource scaling — developer-controlled scaling within guardrails
- Monitoring setup — automatic dashboards and alerts for every service
Developer Portal (Backstage)
- Service catalog — register all services with ownership, docs, dependencies
- Software templates — scaffolding for new services, libraries, pipelines
- Tech Radar — track technology adoption and deprecation
- API documentation — auto-generated from OpenAPI specs
- Cost reporting — per-service cloud costs visible to teams
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 · 88 lines · 41 tokens per session scan A ea567dac52f2
platform-engineer is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 15d ago), licensed MIT. It adds 41 tokens to every session and 872 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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