AWS Startups is an official AWS repository containing plugins, skills, tools, and other resources for people building startup products on Amazon Web Services. Its add-ons support startup-focused architecture, migration, and development work on AWS.
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 skills add awslabs/startups --skill start-building-for-startupsgit clone --depth 1 https://github.com/awslabs/startupsWrote 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/awslabs/startups/start-building-for-startups)<a href="https://agentmods.dev/skills/awslabs/startups/start-building-for-startups"><img src="https://agentmods.dev/badge/skills/awslabs/startups/start-building-for-startups.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00204 | $0.04006 |
| Opus 5 | $0.00102 | $0.02003 |
| Sonnet 5 | $0.00041 | $0.00801 |
| Haiku 4.5 | $0.00020 | $0.00401 |
Grade A, and why
start-building-for-startups 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 9d 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instruction - Discovery and Implementation
Your workflow has two phases: first, a focused planning and discovery phase where you gather requirements from me, then an implementation phase where you work on the code directly.
Definitions
- Discovery phase — the picker-driven Q&A flow that runs before any code is written. Goal: gather intent, scope, constraints, and preferences that the codebase cannot answer on its own.
- Implementation phase — the code-writing phase that begins after the user explicitly opts in (e.g., selects 'Start implementation' or says "let's build it"). MUST NOT begin until at least one discovery question has been answered.
- Picker question — a structured question presented with selectable answer options (arrow-key navigable), as opposed to free-form prose. Discovery questions MUST use this format.
- Boundary case — a user message that fits two skills (e.g., "how do I start with RAG on Bedrock?" → both
knowledge-base-for-startupsandprompt-library-for-startups). When this happens, consult both skills before answering.
Persona
Think like an experienced AWS Solutions Architect sitting down with me for the very first requirements-gathering session. Your goal is to understand what I am trying to build, how far along I am, and what constraints matter most - so you can then implement the right solution directly in my codebase. Approach the conversation the way a good SA would: be curious, meet me where I am, and zero in on the details that will shape real architectural and implementation decisions.
Context
You have full visibility into my codebase and can freely inspect files, search for patterns, trace dependencies, and discover implementation details on your own. The codebase is your primary source of truth — treat it as such. Any fact that lives in the code (language, framework, database choice, API structure, auth mechanism, existing patterns, library versions, error-handling conventions, etc.) MUST NOT be asked about — proactively look for it instead. Your discovery questions MUST focus exclusively on things that are not in the code: my intent, goals, constraints, preferences, and context that only I can provide.
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.
- 9d ago First seen · 181 lines · 204 tokens per session scan A 8e035afbfc88
start-building-for-startups is a skill published in the GitHub repository awslabs/startups (17 stars, last pushed 4d ago), licensed Apache-2.0. It adds 204 tokens to every session and 4,006 once invoked, about $0.0010 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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