BF schedule-planner-cxf
全能出行管家技能 — 处理出行规划/行程安排/出差旅游等场景,整合高德地图(路线/天气/周边)与途牛旅行(机票/酒店/火车票/门票**价格查询与比价**)服务,提供场景识别、智能比价、行程规划与行程网页生成。能力与副作用完整披露:(1) 从环境变量读取 AMAP_API_KEY、TUNIU_API_KEY 用于本次查询调用,不跨会话上传第三方;本技能包不含任何密钥文件;(2) **仅调用查询/搜索类接口**(searchLowestPriceFlight / tuniu_hotel_search / searchLowestPriceTrain / query_cheapest_tickets),**不调用任何下单/预订/支付接口**(不调用 saveOrder/create_order/bookTrain/create_ticket_order),不代订、不代付、不创建订单;(3) **不上传用户 PII**:不向任何第三方发送乘客姓名/身份证号/手机号;预订与支付由用户在途牛/12306 等第三方平台自行完成;(4) 本地生成行程 HTML 与第三方平台跳转二维码(qrcode 库),写入技能 ./output/ 目录(会写入本地磁盘);(5) 可选写用户 Desktop(仅 --desktop flag)、可选启动系统浏览器打开本地文件(仅 --open flag,使用 PowerShell Start-Process);(6) 通过用户本地安装的 tuniu CLI(优先 npx tuniu,shell:false)调用查询接口,仅构造已知 tuniu call 子命令,不执行任意命令;(7) 含 generate-trip-page.js / qrcode.js / query-5city-trip.js / query_trip.js 等辅助脚本。Use when the user asks for 出行规划、行程安排、出差旅游、机票酒店价格比价、生成行程网页,或上传行程需求要求规划。
As a process F 37/100 · Will not run — References files that are not bundled: references/city-guides/
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:159High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…9ZZ/0wAx…8jy/kbhs…gJ5+F2mt…V7I+EoRK…K7A==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:189High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…2YE+3fQp…lVw==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:224High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…4hd+2E8N…oYe/ZdlJy+J3uC…Hmg==",
detector
Files scanned: 22. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7392 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: references/city-guides/
Process rating: all ten parameters 37/100
- 0Tools and files. 1 referenced file(s) missing: references/city-guides/
- 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
- 30Running it twice. 5 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 7392 tokens
- 100Steps. 144 steps
- 100Consistency. Name and required fields are in place
- low 12 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)
- +3Description length 863: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2142 emoji in the instructions: noise for the model
- -35 of 8 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 53 headings
- +3Step-by-step instructions: 144 items
- +4Has examples (25 code blocks)
- +4Reference files are cited in the instructions (1 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.