SKILLEMALL.ai

BF viral-marketing-playbook

You bolted a referral program onto your product and... nothing. People don't share because you asked — they share when the loop is designed into the moment they get value. This playbook is the mechanics of virality, with the math to tell whether a loop will actually compound. What's inside: • Viral loop anatomy — the mechanics behind referral, invite, and content loops • K-factor math — calculate your viral coefficient and model growth scenarios before building • Incentive design — what to offer referrers and referred users (and what quietly kills the loop) • Share triggers — the moments in the user journey where sharing feels natural, not begged • Case studies — how Dropbox, Notion, and Loom built their viral engines 🇨🇳 病毒增长设计 — 病毒循环解剖+K因子计算+激励设计+分享触发时机,含 Dropbox/Notion/Loom 拆解。 🇯🇵 バイラル設計 — バイラルループ解剖、K係数計算、インセンティブ設計、シェアトリガー。Dropbox/Notion/Loom事例。 🇰🇷 바이럴 설계 — 바이럴 루프 해부, K-팩터 계산, 인센티브 설계, 공유 트리거. Dropbox/Notion/Loom 사례. Triggers: "viral marketing" | "viral loop" | "referral program" | "referral marketing" | "K-factor" | "viral coefficient" | "invite system" | "share mechanics" | "network effects" | "growth loop" | "word of mouth" | "病毒营销" | "病毒循环" | "裂变" | "推荐机制" | "バイラル" | "바이럴 마케팅"

ClawHub Agent Skills author: Iris Wei v1.2.0 MIT-0 3 files body ≈ 412 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 33/100 · Will not run — References files that are not bundled: references/en/README.md, references/ja/README.md, references/ko/README.md

ProcedureNotionInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
79/100
safety, quality, tests
Safety 60%
100
Quality 40%
48
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: references/en/README.md, references/ja/README.md, references/ko/README.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1211 chars, limit 1024
  • warning missing-ref reference to a missing file: references/en/README.md
  • warning missing-ref reference to a missing file: references/ja/README.md
  • warning missing-ref reference to a missing file: references/ko/README.md
  • note frontmatter-key unknown frontmatter key "source"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: references/en/README.md, references/ja/README.md, references/ko/README.md
  • 0Tools and files. 3 referenced file(s) missing: references/en/README.md, references/ja/README.md, references/ko/README.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 100Steps. 14 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 412 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 1210: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 12 example trigger phrases
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.

External checks

ClawHub: clean
This is a marketing playbook with no executable code or sensitive access; the only noted issue is a somewhat broad activation phrase.
LLM: benign (high) · VirusTotal: · 10 Jul 2026