SKILLEMALL.ai

AC ahkb-cps

AHKB-CPS — 阿色全息知识库建产系统。Arthur's Holographic Knowledge Base Construction & Production System。统一的本地知识库建产平台,将任意文档构建为全息知识库,再消费为幻灯片、文章、全息脑图等多种产出。Use when the user asks to build a knowledge base, write articles, generate PPT/slides, create mind maps, or any knowledge-related task. Triggers: "知识库", "构建知识库与知识地图", "入库", "写文章", "生成文档", "做PPT", "幻灯片", "演讲", "脑图", "思维导图", "全息脑图", "帮我", "怎么用", "AHKB", "AHKB-CPS".

ClawHub Agent Skills author: ArthurTreeNewBee / 阿色树新风 v0.1.0 MIT-0 80 files body ≈ 1 737 tokens Open the sourceclawhub.ai analyzed 2 d ago

AHKB-CPS — 阿色全息知识库建产系统。Arthur's Holographic Knowledge Base Construction & Production System。统一的本地知识库建产平台,将任意文档构建为全息知识库,再消费为幻灯片、文章、全息脑图等多种产出。Use when the user…

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ReferenceGitHubPowerPointWriting and documentsSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
52/100
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: AHKB-CPS — 阿色全息知识库建产系统。Arthur's Holographic Knowledge Base Constru… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 52/100

    • 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
    • 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. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1737 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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -260 emoji in the instructions: noise for the model
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 403: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (6 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

    External checks

    ClawHub: suspicious
    This is mostly a coherent local knowledge-base tool, but it persistently broadens agent permissions and automatically installs dependencies, so users should review it before installing.
    LLM: suspicious (medium) · 29 Jul 2026