BF quantall-mcp
QuantAll（全A解析）MCP —— 股市全市场向量化计算引擎，为 AI 提供本地 Python 计算环境。 AI 编写向量化代码片段，数秒内完成 5000+ 股票的因子计算、策略回测、IC 分析和 GPU 可视化。 让 AI 从"信息查询者"升级为"数据计算者"——用代码算出客观结果，而非搬运网络观点。 触发：用户明确提到"回测""因子分析""IC分析""选股策略""QuantAll""全A解析"等量化关键词时。 不主动在普通股市聊天中触发，仅在用户有明确量化分析需求时使用。 能力声明：本技能需在用户电脑上创建 Python 虚拟环境（300MB+）、安装 quantall 库、 修改 MCP 配置、启动本地 HTTP 服务（localhost:8686）、创建配置文件和启动脚本。 所有涉及用户电脑的操作，AI 必须事先告知用户并获得同意。 UpdateStock 为可选辅助 MCP（数据库管理，需 tushare API），非 QuantAll 必需。
QuantAll（全A解析）MCP —— 股市全市场向量化计算引擎，为 AI 提供本地 Python 计算环境。 AI 编写向量化代码片段，数秒内完成 5000+ 股票的因子计算、策略回测、IC 分析和 GPU 可视化。 让 AI 从"信息查询者"升级为"数据计算者"——用代码算出客观结果，而非搬运网络观点。…
As a process F 28/100 · Will not run — References files that are not bundled: scripts/DB_setting.json, scripts/run.bat
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 8. 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") - warning
missing-refreference to a missing file: scripts/DB_setting.json - warning
missing-refreference to a missing file: scripts/run.bat - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 28/100
- 0Tools and files. 2 referenced file(s) missing: scripts/DB_setting.json, scripts/run.bat
- 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. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (quantall-mcp) differs from the folder (quant-all-mcp)
- 100Steps. 18 steps
- 100Execution cost. Instruction body is 1802 tokens
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 436: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.