SKILLEMALL.ai
GitHub ↗ RU Sign in

BC LinkedIn Content Creation Skill by Reepl

Manage your LinkedIn presence with Reepl -- create drafts, publish and schedule posts, manage contacts and collections, generate AI images, create carousels, post to Twitter/X, and maintain your voice profile. Requires a Reepl account (reepl.io).

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 6 402 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Manage your LinkedIn presence with Reepl -- create drafts, publish and schedule posts, manage contacts and collections, generate AI images, create carousels…

As a process C 58/100 · Has gaps — weak spots: result and completion, consistency, running it twice

IntegrationYouTubeAI 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
B
79/100
safety, quality, tests
Safety 60%
95
Quality 40%
56
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Exfiltration exfil-send-secrets-to-url SKILL.md:477
    Instruction to send secrets/history to an external endpoint (URL is a reference link, not a destination; the skill's own vendor host)
    Generate an AI image for a LinkedIn post using Google Gemini. Requires the user to have linked their Gemini API key in [Reepl settings](https://app.reepl.io/settings/ai-models-api).
    reference linkvendor-host

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 6402 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 58/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 56 mutating operations with no state check
  • 40Consistency. Frontmatter name (LinkedIn Content Creation Skill by Reepl) differs from the folder (reepl)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6402 tokens
  • 100Steps. 22 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 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 246: enough signal without eating the budget
  • +4Structure: 49 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (39 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.