SKILLEMALL.ai

BB onboard

Use /onboard for a focused Codex onboarding flow that learns basic preferences, picks a first goal, and routes the user to the right next action.

ClawHub Claude Code author: eohmig v1.0.0 MIT-0 2 files body ≈ 3 003 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

Use /onboard for a focused Codex onboarding flow that learns basic preferences, picks a first goal, and routes the user to the right next action.

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
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 65/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 48 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 9 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3003 tokens
    • 100Progress reporting. Reports progress

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 145: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 48 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: suspicious
    The skill is a focused onboarding flow, but it stores the user's name and work context in persistent personal rules by default without explicit consent.
    LLM: suspicious (high) · 19 Sept 2026