SKILLEMALL.ai

AC evolve-self-improving

在当前对话中自动发现 corrections、feature requests、knowledge gaps 和 errors 四类学习信号,并评估其中已经验证、以后可复用的事实、规则、做法和踩坑;用户无需先说“记住”。适用于“不对,实际应该……/that is outdated”“还能不能……/I wish it could……”“原文或现场和理解不符”“命令非零、异常栈、意外输出、超时或连接失败”,也适用于主动要求记住、复盘、纠正、归档或删除。自动发现只启动评估:明确纠正、稳定能力期望、证据闭环或已收敛诊断满足写入条件才保存;临时诉求、猜测、原始报错和未定位事件不写,也不会后台监听或自行改变行为。

ClawHub Agent Skills author: Aaron Sun v1.0.1 MIT-0 3 files body ≈ 990 tokens Open the sourceclawhub.ai analyzed 3 d ago

在当前对话中自动发现 corrections、feature requests、knowledge gaps 和 errors 四类学习信号,并评估其中已经验证、以后可复用的事实、规则、做法和踩坑;用户无需先说“记住”。适用于“不对,实际应该……/that is outdated”“还能不能……/I wish it…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 3. 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 53/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 19 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 990 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
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 304: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    This skill stores carefully filtered local learning notes for future use, with no evidence of hidden network access, credential handling, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 20 Aug 2026