SKILLEMALL.ai

AC Map Customer Micromoments Across Web Analytics & CRM Platforms

Analyze customer journey touchpoints to identify micro-moments of intent, frustration, and buying readiness. Use when the user needs audience behavior maps, emotional trigger extraction, or optimal intervention windows for targeted nurture sequences.

ClawHub Agent Skills author: ncreighton v1.0.0 MIT-0 2 files body ≈ 3 678 tokens Open the sourceclawhub.ai analyzed 3 d ago

Analyze customer journey touchpoints to identify micro-moments of intent, frustration, and buying readiness.

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerInfrastructureMarketingSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
99
Quality 40%
78
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration exfil-webhook-url SKILL.md:150
      Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
      export SLACK_WEBHOOK_URL="https://hooks.slack.com/..."
      placeholder

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 52/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 30Running it twice. 4 mutating operations with no state check
    • 40Consistency. Frontmatter name (Map Customer Micromoments Across Web Analytics & CRM Platforms) differs from the folder (audience-micromoment-mapper)
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 49 steps
    • 100Execution cost. Instruction body is 3678 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 250: enough signal without eating the budget
    • +4Structure: 30 headings
    • +3Step-by-step instructions: 49 items
    • +4Has examples (12 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

    External checks

    ClawHub: suspicious
    This skill is not malicious, but it handles sensitive customer profiling data and can push segments or workflow actions into external systems with weak privacy and approval scoping.
    LLM: suspicious (high) · VirusTotal: · 20 Aug 2026