BF alphagbm-buffett-analysis
Warren Buffett-lens scorecard for any ticker. Scores 4 dimensions 0-100 each (business / circle of competence, moat / durable advantage, management / capital allocation, valuation / fair price vs 10Y treasury) and returns a weighted overall HOLDABLE / WATCHABLE / AVOID verdict. This is NOT a generic fundamental screener — it's Buffett's specific framework mechanically applied: sector simplicity, gross margin + ROE + profit margin thresholds, FCF yield vs treasury, and dividend-continuity as management proxy. Triggers: "Buffett analysis AAPL", "score KO with Buffett lens", "would Buffett buy MSFT", "JNJ Buffett scorecard", "AAPL moat analysis", "fair price vs bonds", "Buffett-style verdict on NVDA", "long-term hold analysis"
Warren Buffett-lens scorecard for any ticker.
As a process F 35/100 · Will not run — References files that are not bundled: ../alphagbm-stock-analysis/, ../alphagbm-company-profile/, ../alphagbm-investment-thesis/
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: 1. 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-stock-analysis/ - warning
missing-refreference to a missing file: ../alphagbm-company-profile/ - warning
missing-refreference to a missing file: ../alphagbm-investment-thesis/ - note
frontmatter-keyunknown frontmatter key "globs"
Process rating: all ten parameters 35/100
- 0Tools and files. 3 referenced file(s) missing: ../alphagbm-stock-analysis/, ../alphagbm-company-profile/, ../alphagbm-investment-thesis/
- 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. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1229 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 7 example trigger phrases
- +3Description length 733: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.