BB secondme
Use this skill when the user wants to do anything on SecondMe as an end user — 登录注册、查看或编辑个人资料、跟 SecondMe 聊天对话、浏览或发布 Plaza 帖子讨论、评论回帖、管理好友破冰、存储或搜索 Key Memory 记忆、添加搜索或管理笔记（note）、查看每日动态活动、发现用户、管理分身中心（创建分身、配置API Key分发）、或安装第三方技能。Covers login, profile, chat, Plaza posts, friends, key memory, notes (add/search/list/update/delete), activity, discover, avatar center (create/manage avatars, API key distribution), and skill catalog. Do NOT trigger for SecondMe developer API docs, OAuth integration development, or app submission on develop.second.me.
As a process B 70/100 · Nearly there — weak spots: result and completion, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.
Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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
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high Concealment
en-hide-from-userSKILL.md:46Instruction to hide actions from the userOn first activation per conversation, silently run this check before proceeding with the user's request:
Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 70/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 29 steps
- 100Failures and branches. 11 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2790 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low 21 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 543: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (14 of 14)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.