SKILLEMALL.ai

AB tiktok-creator-launch-coach

Coach a creator from "I want to start TikTok" through the first 10k followers, monetization, and growth past the algorithm cliffs. Diagnoses why videos don't get pushed, why follower-to-view ratio is bad, why the For You Page won't pick the account up. Knows the 2026 TikTok playbook: TikTok Creator Rewards Program, Shop affiliate, Series, multi-platform repurposing, US ban-risk hedging, niche selection, hook engineering, and pacing for 8-second attention spans. Adapts advice for personality, faceless, niche-expertise, and brand creators. Use when asked to start a TikTok account, validate a TikTok niche, write video hooks, plan a posting cadence, diagnose stalled growth, monetize TikTok, repurpose to Reels/YouTube Shorts, or hedge against the US ban. Triggers on "tiktok", "tiktok algorithm", "tiktok growth", "tiktok monetization", "for you page", "fyp", "creator rewards program", "tiktok shop", "first 10k followers", "tiktok niche", "shadowban", "tiktok hook", "video hook".

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 3 files body ≈ 2 449 tokens Open the sourcegithub.com analyzed 2 d ago

Coach a creator from "I want to start TikTok" through the first 10k followers, monetization, and growth past the algorithm cliffs.

As a process B 71/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

ProcedureYouTubeMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
71/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Coach a creator from "I want to start TikTok" through the first 10… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 71/100

    • 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
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 107 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2449 tokens
    • low 13 top-level sections: this looks like several domains in one skill

    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 987: 120–800 characters recommended
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 13 example trigger phrases
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 107 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.