AB help-you-choose
帮你选 — 选择困难症救星。当用户面临职业选择、感情决策、城市选择等人生抉择时使用此技能。通过苏格拉底式提问和 15 种经典思维框架（第一性原理、SWOT、加权决策矩阵等），一步步引导用户厘清内心真实想法，告别纠结、做出清醒决策。支持交互式可视化分析、决策历史记录和用户偏好画像。触发词包括：帮我选、帮我决定、我该怎么选、纠结、不知道该不该、选择困难、两个都想要。
As a process B 65/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 6. 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 65/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 81 steps
- 100Failures and branches. 14 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3121 tokens
- 100Running it twice. Mutating operations check current state
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)
- +1No license
- +2Single-language instructions
- +3Description length 182: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 81 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.
External checks
ClawHub: suspicious
This is mostly a coherent decision-coaching skill, but it can expose sensitive personal decision details through public report hosting and persistent local profiling without enough safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026