SKILLEMALL.ai

BF alphagbm-hedge-advisor

Scenario-driven hedge recommendations for an existing stock position. Takes ticker + cost basis + purpose, auto-classifies the holding situation (falling knife / bottom-fishing / gain-protection / normal) and returns concrete Long Put, Collar, or Tier-down recommendations with live strikes and premiums from the current option chain. Triggers: "hedge my AAPL", "protect my NVDA gains", "collar strategy MSFT", "long put for TSLA", "how to hedge falling knife COIN", "reduce risk BABA", "lock in gains META", "downside protection", "portfolio hedge", "insurance for position"

ClawHub Agent Skills author: Clement Gu v1.0.0 MIT-0 2 files body ≈ 1 109 tokens Open the sourceclawhub.ai analyzed 15 h ago

Scenario-driven hedge recommendations for an existing stock position.

As a process F 38/100 · Will not run — References files that are not bundled: ../alphagbm-options-strategy/, ../alphagbm-greeks/, ../alphagbm-pnl-simulator/

ProcedureFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: ../alphagbm-options-strategy/, ../alphagbm-greeks/, ../alphagbm-pnl-simulator/
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: ../alphagbm-options-strategy/
  • warning missing-ref reference to a missing file: ../alphagbm-greeks/
  • warning missing-ref reference to a missing file: ../alphagbm-pnl-simulator/
  • note frontmatter-key unknown frontmatter key "globs"

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: ../alphagbm-options-strategy/, ../alphagbm-greeks/, ../alphagbm-pnl-simulator/
  • 0Tools and files. 3 referenced file(s) missing: ../alphagbm-options-strategy/, ../alphagbm-greeks/, ../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
  • 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. 17 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1109 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 575: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This skill is a coherent options-hedging advisor, but it can produce concrete trade-like recommendations without enough user caution or consent controls.
LLM: suspicious (medium) · VirusTotal: · 23 Jul 2026