BD deskpeto
把用户的照片生成为专属 AI 桌宠（ChatGPT/Codex Pet 资源包）、在对话里召唤会动的桌宠卡片、用一条命令让桌宠常驻桌面（跟随 WorkBuddy/Claude Code/CodeBuddy 的任务状态）、协助安装；也可免费安装 DeskPeto 共享广场的社区公开桌宠。当用户说「召唤桌宠」「显示我的宠物」「把照片/头像做成桌面宠物」「在桌面上放一只桌宠」「免费试用一只桌宠」「安装 DeskPeto 宠物包」或询问订单进度时使用。Turn the user's photo into a personal desktop AI pet, summon an animated pet card in-chat, put a pet on the desktop with one command, help install it, or install free community pets from the shared gallery.
把用户的照片生成为专属 AI 桌宠（ChatGPT/Codex Pet 资源包）、在对话里召唤会动的桌宠卡片、用一条命令让桌宠常驻桌面（跟随 WorkBuddy/Claude Code/CodeBuddy 的任务状态）、协助安装；也可免费安装 DeskPeto…
As a process D 43/100 · 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Dangerous commands
cmd-pipe-to-shellSKILL.md:27Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host; quoted — discussed, not commanded)- macOS/Linux：`curl -fsSL 'https://api.deskpeto.com/v1/install/…?t=…' | sh`
vendor-hostquoted -
low Dangerous commands
cmd-pipe-to-shellSKILL.md:46Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host; quoted — discussed, not commanded)- macOS / Linux：`curl -fsSL https://api.deskpeto.com/v1/runner/install | sh`
vendor-hostquoted
Files scanned: 3. 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 43/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 29 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1191 tokens
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
- +2Single-language instructions
- +3Description length 430: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.