SKILLEMALL.ai
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AF skroller

Automated social media content collection and analysis across platforms (Twitter/X, Instagram, TikTok, Reddit, LinkedIn, YouTube, Product Hunt, Medium, GitHub, Pinterest). Use when you need to: (1) scrape public posts programmatically, (2) analyze content by keywords or filters, (3) monitor brand mentions or trends for research, (4) curate content for personal analysis, (5) archive publicly available information, or (6) generate digests from scraped feeds. Always comply with platform ToS and applicable privacy laws.

ClawHub Agent Skills author: X v0.0.1 MIT-0 10 files body ≈ 2 431 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 44/100 · Will not run — References files that are not bundled: assets/selector-cheatsheet.md

AnalyzerGitHubYouTubeMarketingtype 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
91/100
safety, quality, tests
Safety 60%
99
Quality 40%
78
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: assets/selector-cheatsheet.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Exfiltration exfil-secret-in-url references/platform-details.md:200
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
    `https://www.googleapis.com/youtube/v3/search?part=…&q=…&key=…
    placeholder

Files scanned: 10. 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: Automated social media content collection and analysis across plat… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning missing-ref reference to a missing file: assets/selector-cheatsheet.md

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: assets/selector-cheatsheet.md
  • 0Tools and files. 1 referenced file(s) missing: assets/selector-cheatsheet.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 65 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2431 tokens
  • low 12 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 521: enough signal without eating the budget
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 65 items
  • +3Output format is stated explicitly
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
Skroller does what it claims, but it combines broad social-media scraping with anti-bot evasion guidance, raw personal-data persistence, credential/session handling, and unsafe local export commands.
LLM: suspicious (high) · VirusTotal: · 29 May 2026