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 skills/iblai/api/iblai-api-infrastructurenpx skills add iblai/api --skill iblai-api-infrastructuregit clone --depth 1 https://github.com/iblai/apiWrote 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/iblai/api/iblai-api-infrastructure)<a href="https://agentmods.dev/skills/iblai/api/iblai-api-infrastructure"><img src="https://agentmods.dev/badge/skills/iblai/api/iblai-api-infrastructure.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00125 | $0.01139 |
| Opus 5 | $0.00063 | $0.00570 |
| Sonnet 5 | $0.00025 | $0.00228 |
| Haiku 4.5 | $0.00013 | $0.00114 |
Grade A, and why
iblai-api-infrastructure 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 3d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iblai-api-infrastructure
How the ibl.ai platform is deployed and self-hosted on infrastructure you control: the AWS topology, the tooling that provisions it, the SSO wiring for the edX LMS, and the agent-sandbox (claw) gateway servers that back live agent chat.
Unlike the other iblai-api-* skills, this one is not a REST reference — it doesn't
call api.iblai.app, and it needs no IBLAI_ORG / IBLAI_API_KEY. It documents server
provisioning, ssh / CLI / Terraform / Ansible workflows, and provider consoles. Access
to the ibl.ai Docker images and platform codebase requires a license — see
ibl.ai/contact.
When to use
- Standing up the platform on your own AWS account (or an existing server / bare
metal) — start with
references/infra-cli.md, and seereferences/aws-architecture.mdfor the resulting topology. - Launching or rebuilding staging environments from pre-baked AMIs via CI —
references/ami-pipeline.md. - Adding Single Sign-On (Google, Microsoft/Entra, Apple, or a generic OIDC provider)
to the Open edX LMS —
references/edx-sso.md. - Deploying an agent-sandbox gateway (OpenClaw on a VPS/Hetzner, or NVIDIA NemoClaw)
and connecting it to the platform —
references/claw-servers.md.
For the API side — registering a claw instance, storing its device keypair, pushing
config, health checks, and setting an agent's model — use /iblai-api-agent-sandbox.
Deploy the server here, then wire it up there.
Scope note
These guides reference server-level and provider-level surfaces (SSH, systemd, cloud
firewall consoles, the LMS Django admin) because that is the actual deployment mechanism
— this is the ops complement to the endpoint-focused REST skills, not a UI walkthrough of
api.iblai.app.
Reference material
Everything is in references/ — pick the file for the job. Each is self-contained enough
to deploy from:
What ships with it
5 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.
- 3d ago First seen · 71 lines · 125 tokens per session scan A 2a3d625ce873
iblai-api-infrastructure is a skill published in the GitHub repository iblai/api (15 stars, last pushed 5d ago), licensed MIT. It adds 125 tokens to every session and 1,139 once invoked, about $0.0006 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.
Other skills, from other repositories
architecture-diagram
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remote-logs
Use when debugging a deployed app backend. Explains how to fetch build logs and runtime logs using the fusebase remote-logs command. Only applicable to apps with a backend/ folder. For local development, use dev-debug-logs skill instead.
aws-well-architected-review
WHAT — AWS Well-Architected Framework review (6 pillars) — operational excellence, security, reliability, performance, cost, sustainability + WAR process. Checklist for workload evaluation on AWS; complementary to official AWS MCP for live account data.
cloud-design-patterns
WHAT — Vendor-neutral distributed cloud patterns (Retry, Bulkhead, Circuit Breaker, CQRS, Event Sourcing, etc.) abstracted from AWS/Azure/GCP sources — when to apply, tradeoffs, mapping to AWS/GCP/Azure primitives. Offline checklist, no live account required.
release-deploy-reporting
Use ONLY when verification passed AND operator explicitly says "prepare deploy" / "draft deploy" / "ship it"; drafts deploy handoff, captures deploy hash + probes + smoke, advises spec DRAFT→DONE flip. Do NOT auto-invoke; operator triggers explicitly.
firebase-cloud-functions
Use when calling callable functions (httpsCallable), passing data to server-side logic, handling function errors/timeouts, configuring regions, or testing with the Emulator Suite.