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AB position-sizer

Calculate risk-based position sizes for long stock trades. Use when user asks about position sizing, how many shares to buy, risk per trade, Kelly criterion, ATR-based sizing, fractional-share sizing, or portfolio risk allocation. Supports stop-loss distance calculation, volatility scaling, and sector concentration checks.

tradermonty/claude-trading-skills Agent Skills author: tradermonty 6 files · 3 scripts body ≈ 1 778 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Calculate risk-based position sizes for long stock trades.

As a process B 78/100 · Nearly there — weak spots: progress reporting

ProcedureData and analyticsFinancetype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
B
78/100
Nearly there
Progress reporting w 2
0
Tools and files w 18
60
Result and completion w 14
60
the three weakest of ten parameters · all ten

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: 6. 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 78/100

    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 65Failures and branches. 3 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 42 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1778 tokens
    • 100Running it twice. Mutating operations check current state

    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 324: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 42 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.