AB cognition-unblocker
Human+AI cognition-unblocker for real-world decisions: combine the user’s goals and values with structured AI analysis to break cognitive bottlenecks and decision deadlocks. Use when the user feels “卡壳、想不通、很纠结、决策困难、视角局限” 或说 “要不要做 X / 不知道怎么选”，需要在人与 AI 协作下拆解问题本质、拓展多元视角、穷举关键方案，并生成可落地的执行步骤，帮助做出现实可行的选择（不限领域，可用于职场决策、人生选择、项目策略等）。
As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting
How to improve
- 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: 2. 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 65/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 60Failures and branches. 2 branches
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 72 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 935 tokens
- 100Running it twice. No mutating operations
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 324: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 72 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.