BF 小果通达信公式转Python量化
小果通达信公式转Python量化函数库。提供100+核心函数、30+技术指标、12+完整交易策略， 支持将通达信指标公式无缝迁移至Python量化环境，实现策略回测、数据分析与实盘交易信号生成。 触发关键词：通达信、TDX、公式转换、指标迁移、选股公式、技术指标、量化策略、回测、 买卖信号、金叉死叉、MACD、KDJ、RSI、BOLL、SAR、CCI、OBV、DMI、BIAS、WR、VR、 PSY、BRAR、CR、MASS、WAD、ASI、EMV、DPO、CHO、WVAD、TRIX、UOS、VTP、BBI、 EXPMA、ENE、PBX、MIKE、XS、TQN、BBIBOLL、ALLIGAT、GMMA、AMV、CYC、CYS、CYW、 ZIG、BACKSET、PEAK、TROUGH、波段交易、趋势跟踪、超买超卖、主力控盘、筹码分布、 量价配合、股票分析、ETF分析、指数分析、量化投资、程序化交易、小果、xg_quant。
小果通达信公式转Python量化函数库。提供100+核心函数、30+技术指标、12+完整交易策略， 支持将通达信指标公式无缝迁移至Python量化环境，实现策略回测、数据分析与实盘交易信号生成。 触发关键词：通达信、TDX、公式转换、指标迁移、选股公式、技术指标、量化策略、回测、…
As a process F 18/100 · Will not run — 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
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") - warning
body-longSKILL.md body ≈ 44007 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "contact"
Process rating: all ten parameters 18/100
- 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
- 10Execution cost. Instruction body is 44007 tokens: crowds the task out of the window
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 39 mutating operations with no state check
- 40Consistency. Frontmatter name (小果通达信公式转Python量化) differs from the folder (xg-tdx-python)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
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
- +4No input/output examples
- -217 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 415: enough signal without eating the budget
- +4Structure: 36 headings
Quality base 70; lint remarks subtract, signals add up to 100. Result: 47.