SKILLEMALL.ai

AB alphagbm-options-score

Score and rank options contracts for any ticker using AlphaGBM's multi-factor scoring model (liquidity, IV attractiveness, Greeks balance, risk/reward). Returns scored option chains with the best contracts highlighted. Use when: evaluating which option to trade, finding the best strike/expiry, ranking options by quality. Triggers on: "score AAPL options", "best options for NVDA", "which TSLA call should I buy", "option chain for SPY", "rank META puts".

ClawHub Agent Skills author: Clement Gu v1.0.0 MIT-0 2 files body ≈ 1 490 tokens Open the sourceclawhub.ai analyzed 2 d ago

Score and rank options contracts for any ticker using AlphaGBM's multi-factor scoring model (liquidity, IV attractiveness, Greeks balance, risk/reward).

As a process B 73/100 · Nearly there — weak spots: failures and branches, progress reporting

ProcedureSales and CRMtype 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
73/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "globs"

    Process rating: all ten parameters 73/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 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
    • 85Steps. 28 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1490 tokens
    • 100Running it twice. No mutating operations

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +3Description length 456: enough signal without eating the budget
    • +4Structure: 26 headings
    • +3Step-by-step instructions: 28 items
    • +3Output format is stated explicitly
    • +4Has examples (9 code blocks)

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

    External checks

    ClawHub: suspicious
    This skill is transparent about scoring options contracts, but it presents high-risk trading recommendations as best picks without clear financial-advice or uncertainty warnings.
    LLM: suspicious (high) · VirusTotal: · 23 Jul 2026