AD fund-168
基金监控技能。管理自选基金列表，监控场外基金、ETF基金的压力位和支撑位。 支持添加/删除自选基金，自动计算压力位 (智能判断：若 20 日均线×1.05 大于当前价格则输出该值，否则输出当前净值×1.05) 和支撑位 (智能判断：若 20 日均线×0.95 小于当前价格则输出该值，否则输出当前净值×0.95)。 支持独立任务模式（task参数）：每只基金创建独立定时任务，间隔1分钟逐个执行，避免API并发限制。 支持涨跌幅告警：当日涨跌幅超阈值时主动推送。 支持持仓盈亏追踪：记录成本价，自动计算浮动盈亏。 支持备份导出（backup）：将所有任务明细导出为CSV/XLSX表格到本地C盘，方便归档与查看。 支持多渠道推送：企业微信/钉钉/飞书/邮件。 支持系统自检：检查API连通性、数据目录、cron状态。 支持自定义均线周期（5/10/20/30/60日）。 支持Watchlist导入导出。 使用场景：基金监控、自选基金管理、净值提醒、技术分析辅助、盈亏追踪。 触发词：基金监控、自选基金、压力位、支撑位、fund-005、添加基金、删除基金、监控时间、task、backup、备份、导出、涨跌幅、告警、盈亏、持仓、自检
As a process D 44/100 · 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 · 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")
Process rating: all ten parameters 44/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 16 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4159 tokens
- 100Steps. 87 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
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
- +1No license
- +2Single-language instructions
- +3Description length 517: enough signal without eating the budget
- +4Structure: 77 headings
- +3Step-by-step instructions: 87 items
- +4Has examples (37 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.