CF Lottery Data Analysis & Number Generator (DLT)
AI-powered China Sports Lottery "Da Le Tou" (DLT) analysis tool — integrates 10+ methodologies including frequency statistics, omission analysis, trend analysis, odd/even & range analysis, consecutive numbers, span analysis, Monte Carlo simulation, and Python data analysis. Updated 2026 with latest historical draw database refresh and enhanced combination filtering algorithms. Provides scientific number selection and rational betting guidance. Keywords: lottery, DLT, Da Le Tou, number prediction, data analysis, lottery strategy, Chinese lottery, 大乐透, 超级大乐透, 前区, 后区, 追加投注, 胆拖, 选号策略.
AI-powered China Sports Lottery "Da Le Tou" (DLT) analysis tool — integrates 10+ methodologies including frequency statistics, omission analysis, trend…
As a process F 26/100 · No process to follow — weak spots: steps, result and completion, when it triggers
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: AI-powered China Sports Lottery "Da Le Tou" (DLT) analysis tool — … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 26/100
- 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (Lottery Data Analysis & Number Generator (DLT)) differs from the folder (chance-dlt-predictor)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Execution cost. Instruction body is 2389 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 587: enough signal without eating the budget
- +4Structure: 20 headings
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.