BD fn-fpk
飞牛NAS (fnOS) FPK 应用打包开发技能。使用此技能开发和打包飞牛NAS第三方应用（.fpk），包括：Native 应用（Node.js/Python/Java/Go/Shell 等）和 Docker 应用。涵盖整个开发周期：开发环境准备、fnpack 创建项目、manifest 配置、权限/资源配置、用户入口配置（应用入口 app/ui/config + 桌面图标 + 文件右键菜单）、生命周期脚本编写（cmd/main）、向导配置（wizard）、图标规范、CGI 反向代理、统一网关注册/认证、运行时环境（Python/Node.js/Java）、中间件服务（Redis/MinIO/RabbitMQ/MariaDB）、依赖管理、fnpack CLI 打包、appcenter-cli 测试安装、到上架发布；以及飞牛开放平台 Open API 接入（文件授权、页面路由、界面语言/主题、后端平台配置查询、前端 JS SDK @trimjs/web-app）。用户提到"飞牛"、"fnOS"、"FPK"、"飞牛应用"、"开放 API"、"Open API"、"@trimjs/web-app"、"文件授权"、"授权路径"、"trim.file"时触发。
As a process D 47/100 · 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 skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 Dangerous commands
cmd-privilegeSKILL.md:52Privilege escalation / world-writable permissionssudo mv fnpa…d64 /usr/local/bin/fnpack
Files scanned: 2. 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") - warning
body-longSKILL.md body ≈ 11724 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 47/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 40Execution cost. Instruction body is 11724 tokens: crowds the task out of the window
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
- 100Steps. 62 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- low 22 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- -234 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 534: enough signal without eating the budget
- +4Structure: 132 headings
- +3Step-by-step instructions: 62 items
- +4Has examples (83 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.