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AC unipile-linkedin-sdk

LinkedIn integration via Unipile's official Node.js SDK. Send messages, InMail, view profiles, manage connections, create posts, and interact with content. Use for LinkedIn automation, messaging, profile retrieval, connection requests, or post interactions. Trigger phrases: "linkedin api", "scrape linkedin", "linkedin profile", "linkedin posts", "send linkedin message".

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 5 files body ≈ 3 922 tokens Open the sourcegithub.com↗ analyzed 2 d ago

LinkedIn integration via Unipile's official Node.js SDK. Send messages, InMail, view profiles, manage connections, create posts, and interact with content.…

As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

IntegrationGitHubSoftware developmentData and analyticsAI and agentstype 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%
95
Quality 40%
85
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:18
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha512-/s55Jujywdw/Jpan+vsy6…4pq+uOt7…4aQ==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:183
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…9ZZ/0wAx…8jy/kbhs…gJ5+F2mt…V7I+EoRK…K7A==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:213
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…2YE+3fQp…lVw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:248
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…4hd+2E8N…oYe/ZdlJy+J3uC…Hmg==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:286
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…w6M+uprW…rLY/w==",
      detector

    Files scanned: 5. 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: LinkedIn integration via Unipile's official Node.js SDK. Send mess… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 55/100

    • 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. 14 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 32 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3922 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +3Description length 372: enough signal without eating the budget
    • +4Structure: 38 headings
    • +3Step-by-step instructions: 32 items
    • +3Output format is stated explicitly
    • +4Has examples (25 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.