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 robisson/build-like-amazon-agent-skills --skill wb-inventgit clone --depth 1 https://github.com/robisson/build-like-amazon-agent-skillsWrote 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/robisson/build-like-amazon-agent-skills/wb-invent)<a href="https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/wb-invent"><img src="https://agentmods.dev/badge/skills/robisson/build-like-amazon-agent-skills/wb-invent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/robisson/build-like-amazon-agent-skills/wb-invent"><img src="https://agentmods.dev/badge/skills/robisson/build-like-amazon-agent-skills/wb-invent.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00044 | $0.03984 |
| Opus 5 | $0.00022 | $0.01992 |
| Sonnet 5 | $0.00009 | $0.00797 |
| Haiku 4.5 | $0.00004 | $0.00398 |
Grade A, and why
wb-invent 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 10d 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WB-Invent: What Is the Solution? Why This One Over Alternatives?
Overview
Invent is where creative problem-solving happens — but within disciplined constraints. The input is a validated problem statement (from Stage 2). The output is a recommended solution with a clear explanation of why this approach was chosen over alternatives.
The key discipline: you must generate and evaluate at least 3 meaningfully different approaches before selecting one. This prevents the team from anchoring on the first idea (which is usually the most obvious, not the best). Each alternative must be genuinely viable — not a strawman created to make the preferred option look good.
Additionally, every major decision is classified as either a one-way door (irreversible, high-consequence) or a two-way door (reversible, lower-consequence). This classification determines how much analysis and approval is required before proceeding.
When to Use
- After completing Stage 2 (Define) with a validated problem statement
- When the team has jumped to a solution without considering alternatives
- When there's internal disagreement about the right approach
- When evaluating build vs. buy vs. partner decisions
- When a proposed solution feels over-engineered or under-ambitious
Amazon Context
Amazon's Leadership Principle "Invent and Simplify" is paired with Jeff Bezos's concept of Type 1 vs Type 2 decisions:
Type 1 (One-Way Door): Irreversible or nearly irreversible. Consequences are severe if wrong. Examples: choosing a database architecture that data will be locked into, public pricing commitments, acquiring a company, launching a new brand.
Type 2 (Two-Way Door): Reversible at low cost. If wrong, you can walk it back. Examples: UI changes behind a feature flag, A/B tests, internal tool choices, pricing experiments on a small segment.
The failure mode Amazon guards against: treating every decision like a Type 1 decision (analysis paralysis) or treating every decision like a Type 2 decision (reckless speed). Most decisions are Type 2 and should be made quickly by small groups. Type 1 decisions deserve the full rigor of Working Backwards.
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.
- 10d ago First seen · 323 lines · 44 tokens per session scan A c2506303f5d6
wb-invent is a skill published in the GitHub repository robisson/build-like-amazon-agent-skills (15 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 3,984 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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