SKILLEMALL.ai

BC 100m-leads

Alex Hormozi's "$100M Leads: How to Get Strangers To Want To Buy Your Stuff" — the ultimate playbook for generating endless engaged leads. Volume II of Acquisition.com series. Covers 5 use cases: ① Getting your first 5 customers — ("I have zero leads" "how to start" "first client" "warm outreach" "free offers to get started") ② Building an audience through free content — ("content marketing" "grow followers" "social media strategy" "hook retain reward" "go viral") ③ Cold outreach that actually works — ("cold email" "cold DM" "cold call script" "outbound sales" "prospecting") ④ Running paid ads profitably — ("Facebook ads" "Google ads" "ad creative" "landing page" "ROAS" "36:1 return") ⑤ Get others to get leads for you — ("affiliate program" "referral system" "hire lead gen" "agency" "partnerships") Trigger when users say: "100m leads" "Alex Hormozi" "lead generation" "how to get customers" "get more clients" "grow my business" "advertising" "paid ads" "content marketing" "cold outreach" "warm outreach" "Acquisition.com" "engaged leads" "lead magnet" "grand slam offer" "value equation"

ClawHub Agent Skills author: BestBooks v1.0.0 MIT-0 8 files body ≈ 2 260 tokens Open the sourceclawhub.ai analyzed 2 d ago

Alex Hormozi's "$100M Leads: How to Get Strangers To Want To Buy Your Stuff" — the ultimate playbook for generating endless engaged leads.

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureMarketingSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1101 chars, limit 1024

Process rating: all ten parameters 63/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 35 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2260 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 1101: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 42 example trigger phrases
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: clean
This is a marketing advice skill with no executable code, credentials, persistence, or hidden data access, though users should apply its outreach advice carefully and legally.
LLM: benign (high) · VirusTotal: · 8 Jun 2026