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AB finding-gaming-content-creators

Finds gaming content creators on TikTok and YouTube using apidojo's scrapers on Apify. Triggers when the user asks to: find gaming influencers for brand campaigns, discover streamers or gaming YouTubers in a specific game or genre, find TikTok creators posting gaming content, identify gaming micro-influencers for product sponsorships, find gaming creators who review hardware or accessories, build a gaming creator outreach list for a gaming brand or peripheral company, or discover rising gaming creators before they go mainstream. Returns creator handle, platform, subscriber count, avg views, game focus, and engagement signals. Ideal for gaming peripheral brands, energy drink sponsors, game publishers, and esports orgs.

ClawHub Agent Skills author: API Dojo v1.0.0 MIT-0 2 files body ≈ 1 385 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

Finds gaming content creators on TikTok and YouTube using apidojo's scrapers on Apify.

As a process B 78/100 · Nearly there — weak spots: running it twice, progress reporting

AnalyzerYouTubeMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
94
Quality 40%
88
Run on models
none yet
Process rating
B
78/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Failures and branches w 10
50
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 · 6

    ✓ No critical or high findings

    Medium and low: 6
    • low Exfiltration exfil-secret-in-url skill-card.md:37
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      - [TikTok scraper actor run endpoint](https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=…)
      placeholder
    • low Exfiltration exfil-secret-in-url skill-card.md:38
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      - [YouTube scraper actor run endpoint](https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=…)
      placeholder
    • low Exfiltration exfil-secret-in-url SKILL.md:101
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      curl -X POST "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=…"   -H "Content-Type: application/json"   -d '{"keywords": ["#valorant", "#valorantclips", "#gamingtiktok"], "
      placeholder
    • low Exfiltration net-credential-use SKILL.md:101
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -X POST "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=…"   -H "Content-Type: application/json"   -d '{"keywords": ["#valorant", "#valorantclips", "#gamingtiktok"], "
      vendor-host
    • low Exfiltration exfil-secret-in-url SKILL.md:104
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      curl -X POST "https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=…"   -H "Content-Type: application/json"   -d '{"searchKeywords": ["valorant gameplay", "valorant tips 2026"],
      placeholder
    • low Exfiltration net-credential-use SKILL.md:104
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -X POST "https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=…"   -H "Content-Type: application/json"   -d '{"searchKeywords": ["valorant gameplay", "valorant tips 2026"],
      vendor-host

    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 78/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1385 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

    • +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 727: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 9 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: clean
    This skill clearly uses Apify TikTok and YouTube scrapers to find gaming creators, with disclosed token, network, and optional export behavior.
    LLM: benign (high) · VirusTotal: · 3 Sept 2026