BC agent-stock-pro
股市 AI 量化交易 Pro 版，支持选股、交易决策、持仓分析、量化评分、PDF 报告生成、策略跟踪模拟交易等。基于 agent-stock 优化：修复 PDF 中文字体、精简工作流、支持定时任务。
股市 AI 量化交易 Pro 版，支持选股、交易决策、持仓分析、量化评分、PDF 报告生成、策略跟踪模拟交易等。基于 agent-stock 优化：修复 PDF 中文字体、精简工作流、支持定时任务。
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
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: 10. 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 54/100
- 0Result and completion. Does not say what the result is
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 454 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)
- +3Description length 99: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 4 headings
- +3Step-by-step instructions: 5 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (5 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.
External checks
ClawHub: suspicious
The skill is mostly coherent for stock analysis, but it automatically persists simulated portfolio data and can send generated financial reports without clear per-run user approval.
LLM: suspicious (high) · VirusTotal: · 5 Jun 2026