SKILLEMALL.ai

AC analytics-and-reporting

Social media analytics and reporting — read native platform data honestly and turn it into next actions. Use when someone wants to "check my analytics," "see how my posts are doing," "build a social media report," "which content is working," "what metrics/KPIs should I track," or to turn performance data into next steps. Measures goal-mapped SIGNAL metrics (saves, shares, watch time/retention, engagement-rate-by-reach, follower-growth-rate, CTR, conversions) — not vanity (followers/impressions/likes) — and closes the loop. Uses the METER framework. Reads brand-profile + social-strategy (goals) first. WoopSocial has NO analytics surface, so this reads NATIVE platform dashboards (+ GA4/UTM) and interprets numbers the human provides; it NEVER fabricates a metric. Feeds content-recycling, experimentation, competitor-analysis, and every growth skill. Distinct from goals-and-kpis (sets targets) and experimentation (runs tests).

ClawHub Agent Skills author: Social Media Skills v1.0.1 MIT-0 7 files body ≈ 1 145 tokens Open the sourceclawhub.ai analyzed 2 d ago

Social media analytics and reporting — read native platform data honestly and turn it into next actions.

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

AnalyzerGoogle AnalyticsData and analyticstype 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
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. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. No external tools needed
    • 100Steps. 14 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1145 tokens
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 935: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 14 items
    • +4Reference files are cited in the instructions (4 of 4)

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

    External checks

    ClawHub: clean
    This skill gives guidance for honest social media analytics reporting and does not request unusual access, automation, or hidden behavior.
    LLM: benign (high) · VirusTotal: · 27 Jul 2026