SKILLEMALL.ai

AC auto-tweet

Post, search, like, retweet, bookmark, and manage a Twitter/X account via a local twikit-based API server on port 19816. Use when the user asks to tweet, search tweets, check timeline, like/retweet posts, or manage their X account. Replaces openclaw-x with fully auditable open-source Python code.

ClawHub Agent Skills author: chatgptnexus v1.0.0 MIT-0 7 files body ≈ 1 144 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

IntegrationSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
62/100
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

How to improve

    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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 62/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1144 tokens
    • 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
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 297: enough signal without eating the budget
    • +4Structure: 32 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (26 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This skill appears purpose-built for X/Twitter automation, but it gives a local server broad control over a live account with weak safeguards and incomplete upfront disclosure.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026