SKILLEMALL.ai

CD option-valuation-toolkit

Prices options for valuation work — Black-Scholes with a cost-of-delay yield, binomial trees that allow early exercise, dilution-adjusted employee options for the equity bridge, equity in a heavily levered firm valued as a call on firm value, and implied volatility. Use when employee options or warrants must be subtracted before computing value per share, when a distressed or negative-earnings company's equity still trades above zero, when testing whether a patent, licence, undeveloped reserve or expansion right is a real option that deserves a premium, or when early exercise makes a European formula wrong. Triggers on option pricing, Black-Scholes, binomial tree, real options, option to delay, patent as an option, equity as a call option, distress and default probability, employee stock options, dilution, warrants, implied volatility, put-call parity.

lyndonkl/claude Agent Skills author: lyndonkl 2 files · 1 script body ≈ 5 586 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Prices options for valuation work — Black-Scholes with a cost-of-delay yield, binomial trees that allow early exercise, dilution-adjusted employee options for…

As a process D 35/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

GeneratorFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
D
35/100
Unfinished process
Steps w 15
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. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 body-long SKILL.md body ≈ 5586 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 35/100

  • 0Steps. Prose only: no discrete steps
  • 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
  • 30Running it twice. 12 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5586 tokens
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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 864: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.