AD investment-research
智能股票研究分析工具，应多复杂深度的投资研究问题，支持单资产/多资产/行业对比分析，输出不同维度的机构级拆解结论和专业研究报告。 **高频使用场景** - 财务分析 - 分析营收、利润、ROE、增速、财务健康度等 - 估值分析 - 查阅 PE/PB/PS、股息率，对比历史和行业得到估值水平结论 - 技术面分析 - 分析均线、MACD、KDJ、支撑阻力 - 资金面分析 - 分析资金流向、主力/散户资金动向差异 - 情绪面分析 - 分析市场共识和矛盾点、社区和机构观点 - 深度研究 - 生成多维度综合投资研究报告 **适用场景** - "分析下宁德时代的财务" → 财务分析报告 - "茅台估值贵不贵" → 估值分析报告 - "比亚迪技术面" → 技术面分析 - "拓维信息的主力资金流向" → 资金面分析 - "给我宁德时代的深度分析" → 完整研究报告 - "比较下比亚迪和宁德时代" → 行业对比报告 **触发词** 投资分析、基本面、财务、估值、业绩增长、技术面、k线、资金面、情绪面、深度研究、研报、个股、行业对比
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
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
-
medium Exfiltration
net-redirectable-api-keyscripts/tool_client.py:43Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 6. 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") - note
frontmatter-keyunknown frontmatter key "env_vars"
Process rating: all ten parameters 49/100
- 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 (investment-research) differs from the folder (invest-buddy)
- 100Tools and files. No external tools needed
- 100Steps. 62 steps
- 100Execution cost. Instruction body is 1336 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
- +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
- +5Description quotes 6 example trigger phrases
- +3Description length 466: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 62 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (1 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.