BD quant_report
量化策略评估报告生成器。读取 Excel 净值数据（策略净值 + 可选品种净值）， 自动计算 20+ 量化指标、生成 12+ 张专业图表，AI 撰写深度分析文字， 最终输出机构级 PDF（16+ 页）和 Word 策略评估报告。 触发：用户上传 Excel 净值数据并要求生成策略评估报告、分析报告。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ReferenceWordData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 13. 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")
Process rating: all ten parameters 41/100
- 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 (quant_report) differs from the folder (proreport)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 19 steps
- 100Execution cost. Instruction body is 1008 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 150: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: clean
This skill reads user-provided Excel performance data and creates local analysis reports, with no evidence of hidden networking, credential access, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026