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AF linkedin-post

Draft, prepare, and publish LinkedIn feed posts through OpenClaw browser automation. Use when a user wants to turn approved post copy into a real LinkedIn feed post, open the share composer, fill the final body, preview link unfurls, or publish after explicit approval. Also use when recurring LinkedIn posting workflow should be standardized into a safe prepare-then-post flow.

ClawHub Agent Skills author: Kanto(칸토) v1.0.1 MIT-0 3 files body ≈ 780 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 43/100 · Will not run — References files that are not bundled: scripts/linkedin_post.py

GeneratorInfrastructuretype 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%
100
Quality 40%
78
Run on models
none yet
Process rating
F
43/100
Will not run
References files that are not bundled: scripts/linkedin_post.py
Tools and files w 18
0
Result and completion w 14
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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/linkedin_post.py

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: scripts/linkedin_post.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/linkedin_post.py
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (linkedin-post) differs from the folder (linkedin-post-openclaw-browser)
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Failures and branches. 5 branches
  • 85Steps. 28 steps, 2 vague phrases
  • 100Execution cost. Instruction body is 780 tokens
  • 100Running it twice. Mutating operations check current state
  • 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

  • +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 378: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This is a disclosed LinkedIn posting helper; it can publish publicly through a logged-in browser, but that behavior matches its stated purpose and is gated by an explicit publish flag and approval instructions.
LLM: benign (high) · VirusTotal: · 29 May 2026