SKILLEMALL.ai

AC contentstudio

ContentStudio is a tool to schedule social-media posts, manage the social inbox, and pull performance analytics across Facebook, LinkedIn, Twitter/X, Instagram, YouTube, TikTok, Pinterest, Threads, Tumblr, Bluesky, and Google Business Profile. Use when the user wants to list/create/delete/approve posts, find the best time to post, read and reply to DMs, comments and reviews, manage media, audit workspaces, accounts, campaigns, labels, categories, or team-members, or pull analytics reports (top posts, engagement, impressions, follower growth, AI insights, etc.) on their ContentStudio account.

ClawHub Agent Skills author: contentstudio-official v1.4.1 MIT-0 5 files body ≈ 19 124 tokens Open the sourceclawhub.ai analyzed 2 d ago

ContentStudio is a tool to schedule social-media posts, manage the social inbox, and pull performance analytics across Facebook, LinkedIn, Twitter/X…

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost

IntegrationYouTubeData and analyticsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Execution cost w 6
10
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 19124 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 62/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 10Execution cost. Instruction body is 19124 tokens: crowds the task out of the window
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 115 steps, 3 vague phrases
  • 100Failures and branches. 7 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (76 tags): a typed call is more reliable

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
  • +2Single-language instructions
  • +3Description length 598: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 115 items
  • +4Has examples (35 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill fits ContentStudio automation, but it needs review because it installs an unpinned global CLI with authority to post, delete, approve, message customers, and manage account/workspace data.
LLM: suspicious (high) · 9 Sept 2026