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.
git clone --depth 1 https://github.com/kumaran-is/claude-code-onboardingWrote 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/commands/kumaran-is/claude-code-onboarding/scaffold-agentic-ai)<a href="https://agentmods.dev/commands/kumaran-is/claude-code-onboarding/scaffold-agentic-ai"><img src="https://agentmods.dev/badge/commands/kumaran-is/claude-code-onboarding/scaffold-agentic-ai.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 5.1 | $0.00045 | $0.00274 |
| Opus 5 | $0.00023 | $0.00137 |
| Sonnet 5 | $0.00009 | $0.00055 |
| Haiku 4.5 | $0.00005 | $0.00027 |
Grade A, and why
scaffold-agentic-ai 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 4d 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
Scaffold Agentic AI Service
Project name: $ARGUMENTS (default to "my-agent-service" if not provided)
Delegate to the agentic-ai-dev skill for all patterns, templates, and reference files.
Steps
- Read the
agentic-ai-devskill and its reference files for exact code templates - Initialize project —
uv init $ARGUMENTS --python 3.14 - Add production + dev dependencies per skill reference
agentic-config-project.md - Create directory structure under
src/<service_name>/per skill conventions - Create core modules (config, logging, exceptions), agent layer (state, tools, nodes, graph), LLM providers, API layer (FastAPI + routes), and tests using skill reference templates
- Add infrastructure (Dockerfile, docker-compose.dev.yml, .env)
- Verify —
ruff check src/andmypy src/
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.
- 4d ago First seen · 23 lines · 45 tokens per session scan A bdda62c5e5dc
scaffold-agentic-ai is a command published in the GitHub repository kumaran-is/claude-code-onboarding (35 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 274 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 2026-09-03.
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