SKILLEMALL.ai

AB investing-vocabulary-explainer

Use when asked what a term means in an annual report, to explain EBITDA, goodwill, free cash flow, working capital or diluted EPS, or to define any investing or accounting word in plain English, ideally in the context of an uploaded report. Explains each term the user gives, anchored to the specific document where one is provided. Produces, per term, a one-sentence plain definition, where it appears in this document with the page, why a beginner might misread it, and one thing to check next. Refuses buy, sell and valuation opinions and points to the other skills in the bundle instead. Educational, not financial advice.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 1 584 tokens Open the sourcegithub.com analyzed 14 h ago

Use when asked what a term means in an annual report, to explain EBITDA, goodwill, free cash flow, working capital or diluted EPS, or to define any investing…

As a process B 66/100 · Nearly there — weak spots: failures and branches, progress reporting

GeneratorFinanceData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
66/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Tools and files w 18
60
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: investing-vocabulary-explainer (mohitagw15856/pm-claude-skills)

How to improve

    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: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 66/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 30 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1584 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 626: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 30 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.