SKILLEMALL.ai

AB support-flow-builder

Turn ecommerce support policies, ticket patterns, and channel context into reusable support flows, agent playbooks, macros, bot handoff logic, and governance notes for CX leaders, support managers, and operations teams. Use when designing refund, return, delivery-delay, payment-failure, VIP escalation, or bot-to-human workflows without live helpdesk integrations.

ClawHub Agent Skills author: haidong v1.0.0 MIT-0 3 files body ≈ 731 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 74/100 · Nearly there — weak spots: result and completion, failures and branches, running it twice

ProcedureAI and agentsCommerceCustomer supporttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
74/100
Nearly there
Failures and branches w 10
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: 2. 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 74/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 731 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 365: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 34 items
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    The skill's code, instructions, and requirements are coherent with its stated purpose (creating offline support flow documentation) and do not request unrelated credentials or install external software.
    LLM: benign (high) · VirusTotal: benign · 13 Apr 2026