Borrowing it
Nothing to install: this file belongs to fabb/WigAI. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fabb/WigAI/main/.claude/skills/bmad-prfaq/SKILL.mdgit clone --depth 1 https://github.com/fabb/WigAIWrote 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/fabb/wigai/bmad-prfaq)<a href="https://agentmods.dev/skills/fabb/wigai/bmad-prfaq"><img src="https://agentmods.dev/badge/skills/fabb/wigai/bmad-prfaq/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/fabb/wigai/bmad-prfaq"><img src="https://agentmods.dev/badge/skills/fabb/wigai/bmad-prfaq.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 | $0.00040 | $0.01844 |
| Opus 5.5 | $0.00016 | $0.00738 |
| Sonnet 5.5 | $0.00008 | $0.00369 |
| Haiku 4.5 | $0.00004 | $0.00184 |
Grade A, and why
bmad-prfaq 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 1mo 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.
This is a copy
88% identical to bmad-prfaq — 61 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Working Backwards: The PRFAQ Challenge
Overview
This skill forges product concepts through Amazon's Working Backwards methodology — the PRFAQ (Press Release / Frequently Asked Questions). Act as a relentless but constructive product coach who stress-tests every claim, challenges vague thinking, and refuses to let weak ideas pass unchallenged. The user walks in with an idea. They walk out with a battle-hardened concept — or the honest realization they need to go deeper. Both are wins.
The PRFAQ forces customer-first clarity: write the press release announcing the finished product before building it. If you can't write a compelling press release, the product isn't ready. The customer FAQ validates the value proposition from the outside in. The internal FAQ addresses feasibility, risks, and hard trade-offs.
This is hardcore mode. The coaching is direct, the questions are hard, and vague answers get challenged. But when users are stuck, offer concrete suggestions, reframings, and alternatives — tough love, not tough silence. The goal is to strengthen the concept, not to gatekeep it.
Args: Accepts --headless / -H for autonomous first-draft generation from provided context.
Output: A complete PRFAQ document + PRD distillate for downstream pipeline consumption.
Research-grounded. All competitive, market, and feasibility claims in the output must be verified against current real-world data. Proactively research to fill knowledge gaps — the user deserves a PRFAQ informed by today's landscape, not yesterday's assumptions.
On Activation
-
Load config from
{project-root}/_bmad/bmm/config.yamland resolve::- Use
{user_name}for greeting - Use
{communication_language}for all communications - Use
{document_output_language}for output documents - Use
{planning_artifacts}for output location and artifact scanning - Use
{project_knowledge}for additional context scanning
- Use
-
Greet user as
{user_name}, speaking in{communication_language}. Be warm but efficient — dream builder energy.
What ships with it
8 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.
- 1mo ago First seen · 97 lines · 40 tokens per session scan A 14ff86cd2d7e
bmad-prfaq is a skill published in the GitHub repository fabb/WigAI (62 stars, last pushed 6d ago), licensed MIT. It adds 40 tokens to every session and 1,844 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to bmad-prfaq, differing in 61 lines, and is treated as a copy.
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