SKILLEMALL.ai

AB customer-relationship-ladder

Activate when: a key account renewal is at risk and the team can't explain why the customer values them; someone asks 'how do we become a strategic partner?'; a CSM needs to know where a relationship actually stands; the team claims to be strategic but has no proactive insight delivery this quarter; a deal was lost on relationship despite having the best product. Do NOT activate when: the customer base is transactional high-volume with ACV under $500 (Rung 3–5 is structurally impossible); the customer explicitly prefers arms-length vendor relationships. More: deciqai.com/c/customer-relationship-ladder

ClawHub Agent Skills author: deciqAI v1.0.4 MIT-0 4 files body ≈ 1 983 tokens Open the sourceclawhub.ai analyzed 2 d ago

Activate when: a key account renewal is at risk and the team can't explain why the customer values them; someone asks 'how do we become a strategic partner?'…

As a process B 67/100 · Nearly there — weak spots: when it triggers, failures and branches, running it twice

ProcedureData and analyticsAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
67/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
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: 4. 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 67/100

    • 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. 3 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1983 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 608: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This is a plain coaching framework for assessing B2B customer relationships and does not request unusual access or hidden behavior.
    LLM: benign (high) · VirusTotal: · 16 Jul 2026