SKILLEMALL.ai

AB skill-merge-and-republish

Merge overlapping local skills into one canonical skill and republish the canonical skill to ClawHub. Use when two local skills have overlapping responsibilities, when a temporary helper skill should be folded back into a stronger existing skill, or when the user asks to merge duplicated skills and update ClawHub after the merge.

ClawHub Agent Skills author: G-Hanasq v0.1.0 MIT-0 2 files body ≈ 439 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
B
65/100
Nearly there
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
    • 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

    • 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. 8 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 439 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • high The skill tells the model to perform an irreversible action with no human approval

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 331: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 35 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: suspicious
    This looks like a purpose-aligned local skill-management workflow, but it needs review because it can remove a local skill folder without a clearly documented confirmation or backup safeguard.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026