SKILLEMALL.ai

AB Physical Mail Action Sorter

Sort a stressful stack of physical mail into four bins with action labels, discard/archive rules, and a simple action tracker.

ClawHub Agent Skills author: haidong v1.0.1 MIT-0 3 files body ≈ 1 749 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 77/100 · Nearly there — weak spots: consistency, running it twice

ProcedureAI and agentsSoftware developmentFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
B
77/100
Nearly there
Running it twice w 4
30
Consistency w 8
40
Result and completion w 14
60
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: 3. 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 "type"

    Process rating: all ten parameters 77/100

    • 30Running it twice. 16 mutating operations with no state check
    • 40Consistency. Frontmatter name (Physical Mail Action Sorter) differs from the folder (physical-mail-action-sorter)
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 4 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 44 steps
    • 100Execution cost. Instruction body is 1749 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The skill ranks results itself: that belongs to the system behind the tool, not the model

    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 126: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 44 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This is a prompt-only mail-sorting helper with clear privacy limits and no evidence of code execution, credentials, persistence, or network access.
    LLM: benign (high) · VirusTotal: benign · 13 May 2026