BF alphagbm-bps-backtest
Full walk-forward Bull Put Spread backtest over ~8 years of daily history. Runs both the signal (FearScore ≥ 60 entry) version AND a no-signal control in the same request, so you can quantify whether the fear-entry rule actually delivers alpha for this ticker under your parameters. Returns equity curve, 4 KPIs (annualized return / win rate / max drawdown / Sharpe), trade ledger, and a plain-language takeaway. Triggers: "backtest BPS on QQQ", "bull put spread backtest", "does FearScore work on SPY", "what DTE for BPS", "optimal bull put spread delta", "BPS strategy backtest", "credit spread backtest", "backtest short put spread"
Full walk-forward Bull Put Spread backtest over ~8 years of daily history.
As a process F 35/100 · Will not run — References files that are not bundled: ../alphagbm-fear-score/, ../alphagbm-options-strategy/, ../alphagbm-pnl-simulator/
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: ../alphagbm-fear-score/ - warning
missing-refreference to a missing file: ../alphagbm-options-strategy/ - warning
missing-refreference to a missing file: ../alphagbm-pnl-simulator/ - note
frontmatter-keyunknown frontmatter key "globs"
Process rating: all ten parameters 35/100
- 0Tools and files. 3 referenced file(s) missing: ../alphagbm-fear-score/, ../alphagbm-options-strategy/, ../alphagbm-pnl-simulator/
- 0Result and completion. Does not say what the result is
- 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
- 20When it triggers. No condition that starts the skill
- 100Steps. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1194 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 635: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.