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AF linkedin-post-generator

Generate high-quality LinkedIn posts locally from a short prompt, topic, or outline. Use when the user asks to draft, rewrite, or improve a LinkedIn post, headline, or caption, including adding hooks, CTAs, or tailoring tone and length.

ClawHub Agent Skills author: Ksrinivas2304 v1.0.0 MIT-0 2 files body ≈ 1 745 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 55/100 · Will not run — References files that are not bundled: scripts/generate_post.py

GeneratorAI and agentsInfrastructuretype 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
55/100
Will not run
References files that are not bundled: scripts/generate_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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

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

Process rating: all ten parameters 55/100

Will not run. References files that are not bundled: scripts/generate_post.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/generate_post.py
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (linkedin-post-generator) differs from the folder (linkedin-post-generator-nivas)
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 86 steps, 2 vague phrases
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 8 branches, has a failure section
  • 100Execution cost. Instruction body is 1745 tokens
  • 100Running it twice. No mutating operations
  • 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 236: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 86 items
  • +4Has examples (0 code blocks)

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

External checks

ClawHub: clean
This is a local writing helper for LinkedIn posts and does not request account access, credentials, network posting, persistence, or broad file permissions.
LLM: benign (high) · VirusTotal: · 29 May 2026