SKILLEMALL.ai

AA analyzing-competitor-tiktok-content-strategy

Analyzes a competitor's TikTok content strategy and top-performing videos using apidojo's scrapers on Apify. Triggers when the user asks to: see what content a competitor posts on TikTok, analyze which TikTok videos perform best for a brand, reverse-engineer a competitor's TikTok strategy, find out how often a competitor posts and what gets the most engagement, study a brand's TikTok presence, compare TikTok content strategies across competing brands, or find out what topics a competitor covers on TikTok. Returns video topics, post frequency, avg views, top hooks, hashtags used, and engagement patterns. Ideal for social media strategists, content teams, and competitive intelligence analysts.

ClawHub Agent Skills author: API Dojo v0.1.0 MIT-0 2 files body ≈ 1 506 tokens Open the sourceclawhub.ai analyzed 2 d ago

Analyzes a competitor's TikTok content strategy and top-performing videos using apidojo's scrapers on Apify.

As a process A 84/100 · Runs to the end — weak spots: progress reporting

AnalyzerMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
88
Run on models
none yet
Process rating
A
84/100
Runs to the end
Progress reporting w 2
0
Failures and branches w 10
50
Result and completion w 14
60
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration exfil-secret-in-url SKILL.md:94
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      "https://api.apify.com/v2/acts/apidojo~tiktok-profile-scraper/runs?token=…" \
      placeholder
    • low Exfiltration exfil-secret-in-url SKILL.md:116
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=…" \
      placeholder

    Files scanned: 2. 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 84/100

    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 11 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1506 tokens
    • 100Running it twice. No mutating operations

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +3Description length 700: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 11 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    The skill mostly does what it claims, but it exposes an overbroad custom JavaScript option and broad scraping inputs that users should review before installing.
    LLM: suspicious (high) · VirusTotal: · 3 Sept 2026