BC noah-stock-trade
用于股票交易相关的订单、成交、可买可卖数量、订单详情、订单费用、下单前费用预估，以及账户、持仓、证券资产、资金流水等场景。当用户询问今日订单、历史订单、今日成交、历史成交、订单状态、订单详情、费用明细、可买可卖数量、融资最大可买数量、账户信息、当前持仓、证券资产、资金流水、组合概览、交易前评估时使用。优先通过统一 CLI / 脚本入口执行查询与评估，不要让 agent 直接手拼交易接口。当前默认只开放只读查询与交易前评估；真实下单、改单、撤单属于高风险写操作，当前不对外承诺。
As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
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/config.py:42Helper 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: 19. 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 55/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 104 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 917 tokens
- 100Running it twice. No mutating operations
- low 11 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)
- +4No input/output examples
- -35 of 8 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 240: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 104 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (6 of 8)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.