SKILLEMALL.ai
GitHub ↗ RU Sign in

BC sentiment-compass

Sentiment Compass — AI-powered social media sentiment monitoring & analysis tool. Monitors Xiaohongshu, Douyin, Weibo, WeChat Official Accounts for keyword mentions. AI sentiment analysis (🟢positive / 🟡neutral / 🔴negative), auto-generated sentiment reports, Feishu/email alerts when negative threshold exceeded. Triggers: sentiment, sentiment monitoring, social media monitoring, sentiment analysis, brand monitoring, negative alerts, social media monitoring

ClawHub Agent Skills author: YK-Global v1.0.0 MIT-0 9 files · 4 scripts body ≈ 2 402 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Sentiment Compass — AI-powered social media sentiment monitoring & analysis tool.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerPlaywrightInfrastructureMarketingtype 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
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
51/100
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "override-tools"

    Process rating: all ten parameters 51/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 11 mutating operations with no state check
    • 40Consistency. Frontmatter name (sentiment-compass) differs from the folder (sentiment-analysis-compass)
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 20 steps
    • 100Execution cost. Instruction body is 2402 tokens
    • low 14 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 461: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (13 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The skill largely matches its stated monitoring purpose, but it needs Review because it stores credentials insecurely and can send monitored content, alerts, and subscription tokens to external services with weak disclosure and controls.
    LLM: suspicious (high) · VirusTotal: benign · 16 Sept 2026