SKILLEMALL.ai

AC twitter-autopilot

Search X Twitter data, monitor accounts, track trends, and publish posts through the AISA relay. Use when: the user needs Twitter search, social listening, influencer monitoring, posting, reply, like, or follow workflows.

ClawHub Agent Skills author: AIsa v1.0.0 MIT-0 7 files body ≈ 378 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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

    • note frontmatter-key unknown frontmatter key "primaryEnv"
    • note frontmatter-key unknown frontmatter key "requires"

    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
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (twitter-autopilot) differs from the folder (twitter-autopilot-aisa)
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 11 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Execution cost. Instruction body is 378 tokens

    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 221: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (2 code blocks)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This Twitter/X automation skill is mostly purpose-aligned, but it exposes the configured API key in normal command output and can perform public account actions.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026