SKILLEMALL.ai

BC 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)。

ClawHub Agent Skills author: banshui v1.0.8 MIT-0 2 files body ≈ 935 tokens Open the sourceclawhub.ai↗ analyzed 12 d ago

Human+AI cognition-unblocker for real-world decisions: combine the user’s goals and values with structured AI analysis to break cognitive bottlenecks and…

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

Analyzertype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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: 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 63/100

    • 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
    • 85Steps. 72 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 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.

    External checks

    ClawHub: clean
    This skill is a disclosed decision-support prompt workflow with no code execution, data access, persistence, or hidden behavior.
    LLM: benign (high) · VirusTotal: · 12 Sept 2026