SKILLEMALL.ai

AC interactive-content

The participation content format — polls, quizzes, Q&A / scoped AMAs, this-or-that, emoji sliders, question boxes, caption-this, Add-Yours, and challenges. Use when someone wants interactive posts, Story stickers, a poll/quiz/AMA, a challenge or contest, or to turn passive scrollers into participants. Low-friction taps are high-value algorithmic signals, and every interaction doubles as audience research. Uses the REACT framework. Reads brand-profile + audience-research + voice-builder first. The agent designs the mechanic, questions, copy, and the close-the-loop plan; the HUMAN adds native interactive elements in-app — stickers and live AMAs are NATIVE-ONLY (WoopSocial cannot attach stickers or read results); WoopSocial publishes the feed-post versions. NEVER fabricates or rigs results or fakes participation; consent before sharing anyone's answer. Distinct from community-management, reply-and-comment-writer, livestream-and-realtime, and ugc-and-influencer.

ClawHub Agent Skills author: Social Media Skills v1.0.1 MIT-0 7 files body ≈ 1 776 tokens Open the sourceclawhub.ai analyzed 2 d ago

The participation content format — polls, quizzes, Q&A / scoped AMAs, this-or-that, emoji sliders, question boxes, caption-this, Add-Yours, and challenges.

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerMarketingLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 6. 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 56/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1776 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low No test case covers injection arriving through data

    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)
    • +3Description length 972: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 9 items
    • +4Reference files are cited in the instructions (3 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This skill is a disclosed content-planning guide for interactive social posts, with human-controlled native actions and no executable install behavior.
    LLM: benign (high) · VirusTotal: · 27 Jul 2026