BD 行情研判（云端版）
每日A股行情研判编排器（纯云端版，无需MCP连接器，无需电脑开机）。分步执行：日历检查→行情数据→新闻简报→持股诊断→自选股分析→ERP计算→组装报告→上传IMA知识库。运行前请确保已安装依赖技能：stock-price-query-mx、tecent-finance、eastmoney-mx-skills-suite、china-stock-data。
每日A股行情研判编排器（纯云端版，无需MCP连接器，无需电脑开机）。分步执行：日历检查→行情数据→新闻简报→持股诊断→自选股分析→ERP计算→组装报告→上传IMA知识库。运行前请确保已安装依赖技能：stock-price-query-mx、tecent-finance、eastmoney-mx-skills-suit…
As a process D 41/100 · 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.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:39High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| `MX_APIKEY` | `em_6…puk` | 东方财富妙想 API Key（诊股/PE/国债数据源） |
table
Files scanned: 4. 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") - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "triggers"
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 (行情研判（云端版）) differs from the folder (market-analysis-cloud)
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 15 steps
- 100Execution cost. Instruction body is 2360 tokens
- 100Running it twice. No mutating operations
- low 13 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
- -213 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 178: enough signal without eating the budget
- +4Structure: 50 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.