BD hs300-research-v5
沪深300多因子投研系统 v6.0 — 多策略量化选股平台。每当用户要求分析A股、沪深300、 多因子选股、投研日报、股票评分、个股基本面/技术面分析时，必须使用此技能。 新增9大策略体系：宽基指增(沪深300/500/1000)、主动量化(多策略复合/空气指增/成长期优选)、 高频量价(16因子月频/周频)、特色策略(科创板)。支持策略相关性分析、绩效对比、资产配置建议。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 76. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (hs300-research-v5) differs from the folder (hs300-research-v6)
- 100Tools and files. No external tools needed
- 100Steps. 26 steps
- 100Execution cost. Instruction body is 1429 tokens
- low 15 top-level sections: this looks like several domains in one skill
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 188: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (13 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.
External checks
ClawHub: suspicious
This finance skill mostly matches its research purpose, but it ships hardcoded third-party credentials and has misleading data-source and analysis-scope claims that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026