SKILLEMALL.ai

AC options-payoff-calculator

Options payoff calculator for stocks and ETFs, pre-loaded with the ticker's own market data instead of hand typed inputs: an interactive profit and loss chart at expiry for long calls, long puts, covered calls, cash secured puts, bull call spreads, bear put spreads, straddles, strangles and iron condors, with breakevens, max profit, max loss and the expected move band drawn in behind the curve. The 15 minute delayed last price, implied volatility at 30, 60 and 90 days, the 25 delta skew, the IV rank and the next earnings date are bound in at build time. Premiums are modeled with Black-Scholes from end of day implied volatility, not quoted from a live options chain. Renders offline, no live call at view time. Use for options payoff calculator, options payoff diagram, options profit calculator, options P/L chart, covered call calculator, vertical spread calculator, straddle payoff, iron condor calculator, options breakeven calculator. Read-only. No trading, no purchases, no write operations, no wallet access.

ClawHub Agent Skills author: Senti v1.0.3 MIT-0 4 files body ≈ 4 376 tokens Open the sourceclawhub.ai analyzed 3 d ago

Options payoff calculator for stocks and ETFs, pre-loaded with the ticker's own market data instead of hand typed inputs: an interactive profit and loss chart…

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
81
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration net-credential-use SKILL.md:117
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -H "X-SentiSense-API-Key: $SENTISENSE_API_KEY" \
      security skill

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "requires"
    • note frontmatter-key unknown frontmatter key "primaryEnv"

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4376 tokens
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 top-level sections: this looks like several domains in one skill

    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)
    • +3Description length 1022: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (4 code blocks)
    • +3All 1 scripts are documented

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

    External checks

    ClawHub: clean
    This skill coherently fetches read-only market data and produces a local options payoff HTML file, with one documented manual binding caveat users should avoid.
    LLM: benign (high) · VirusTotal: · 8 Sept 2026