AC stock-research-engine
个股基本面深度研究引擎。当用户输入股票代码、公司名称或要求分析某只股票时触发。覆盖A股、港股、美股。输出买方基金经理视角的投资分析简报，包含市场情绪、基本面、管理层评估、业务拆解、催化剂日历、风险提示和估值数据展示。任何涉及"帮我看看这个票"、"分析一下XXX"、"这个公司怎么样"、"XXX值不值得买"、股票代码（如600519、00700.HK、AAPL）等表述时，都应使用此skill。也适用于用户要求批量快速学习多个标的基本面的场景。
As a process C 53/100 · Has gaps — 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: 4. 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 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 20 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 293 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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 221: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 20 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: clean
This is an instruction-only stock research skill that may look up public market information, but it does not request code execution, credentials, persistence, or account-changing authority.
LLM: benign (high) · VirusTotal: · 29 May 2026