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AD yunlv-linkedin-outreach

Use when user needs to generate personalized LinkedIn connection requests or outreach messages. Use when automating LinkedIn lead generation and engagement. Use when writing professional B2B messages for LinkedIn prospects. Use when user mentions "LinkedIn开发信", "领英触达", "LinkedIn消息", "社交获客", "连接请求", "领英营销".

ClawHub Agent Skills author: WangM-A3 v1.0.3 MIT-0 6 files body ≈ 1 205 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSales and CRMtype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "progressive"
    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 49/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (yunlv-linkedin-outreach) differs from the folder (skill-linkedin)
    • 100Tools and files. No external tools needed
    • 100Steps. 42 steps
    • 100Execution cost. Instruction body is 1205 tokens
    • 100Running it twice. No mutating operations
    • low 10 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)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 307: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 42 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This LinkedIn outreach skill has a coherent purpose, but it needs Review because it combines sensitive LinkedIn credentials, automated outreach, and stored prospect data without enough scoping or retention safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026