AF alphagbm-take-profit
Quantifies whether a stock is suitable for long-term holding or requires tiered profit-taking — using a novel "rollercoaster rate" metric (probability that an entry's paper profit reaches +50% then falls back >50% from peak before exit). Runs 15 exit strategies over ~10 years of daily history per ticker and returns medians for each. First query for a new ticker takes ~30s and gets cached globally; subsequent queries are instant. Triggers: "should I hold TQQQ long-term", "take-profit strategy for NVDA", "is AAPL holdable", "rollercoaster rate for TSLA", "sell strategy COIN", "when to sell NVDA", "profit-taking plan for QQQ", "exit strategy for my stock", "leveraged ETF hold analysis"
Quantifies whether a stock is suitable for long-term holding or requires tiered profit-taking — using a novel "rollercoaster rate" metric (probability that an…
As a process F 38/100 · Will not run — References files that are not bundled: ../alphagbm-stock-analysis/, ../alphagbm-watchlist/, ../alphagbm-hedge-advisor/
How to improve
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: ../alphagbm-stock-analysis/ - warning
missing-refreference to a missing file: ../alphagbm-watchlist/ - warning
missing-refreference to a missing file: ../alphagbm-hedge-advisor/ - note
frontmatter-keyunknown frontmatter key "globs"
Process rating: all ten parameters 38/100
- 0Tools and files. 3 referenced file(s) missing: ../alphagbm-stock-analysis/, ../alphagbm-watchlist/, ../alphagbm-hedge-advisor/
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 85Steps. 29 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1236 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 10 example trigger phrases
- +3Description length 691: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.