SKILLEMALL.ai

BC social0

Create, schedule, and publish social media posts across Instagram, TikTok, YouTube, X, LinkedIn, Facebook, Pinterest, Threads, and Bluesky via the Social0 CLI (preferred) or MCP. Covers account listing, media upload, drafts, instant publish, scheduling, and per-platform publish status.

ClawHub Agent Skills author: Abhishek B R v1.0.1 MIT-0 2 files body ≈ 2 609 tokens Open the sourceclawhub.ai analyzed 2 d ago

Create, schedule, and publish social media posts across Instagram, TikTok, YouTube, X, LinkedIn, Facebook, Pinterest, Threads, and Bluesky via the Social0 CLI…

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

GeneratorYouTubeGitHubAI and agentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "last-updated"
  • note edit-residue the text marks something as outdated (lines 237): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 58/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 37 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 85Steps. 37 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2609 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 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

  • +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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 286: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill clearly describes a Social0 integration for drafting, scheduling, and publishing social media posts, with sensitive actions disclosed and proportionate to that purpose.
LLM: benign (high) · VirusTotal: · 16 Jul 2026