SKILLEMALL.ai

AC zero-to-one

Peter Thiel's "Zero to One" — an executable toolkit for building startups that create new things, from contrarian thinking to monopoly strategy to founding teams. Covers 5 use cases: ① Startup Strategy — ("How to build a lasting company" "How to find a business idea that matters") ② Monopoly Thinking — ("How to dominate a market" "How to avoid competition") ③ Contrarian Ideas — ("What no one else is building" "How to think differently about business") ④ Founding Teams — ("How to choose a co-founder" "How to build a strong team culture") ⑤ Sales & Distribution — ("How to sell your product" "How to distribute to customers") Trigger when users say: "Zero to One" "Peter Thiel" "How to start a startup" "Monopoly" "Contrarian thinking" "Last mover advantage" "Secrets" "Power law" or mention: startups / technology / innovation / monopoly / competition / Thiel / PayPal / Tesla / cleantech / venture capital / founding team.

ClawHub Agent Skills author: BestBooks v1.0.0 MIT-0 8 files body ≈ 2 228 tokens Open the sourceclawhub.ai analyzed 13 h ago

Peter Thiel's "Zero to One" — an executable toolkit for building startups that create new things, from contrarian thinking to monopoly strategy to founding…

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

GeneratorWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
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

    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

    ✓ No remarks against the Agent Skills spec

    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. 4 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. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2228 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 928: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 19 example trigger phrases
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 33 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: 91.

    External checks

    ClawHub: clean
    No malware or exfiltration signal was provided, and the only noted issue is broad activation wording rather than harmful behavior.
    LLM: benign (low) · VirusTotal: · 8 Jun 2026