SKILLEMALL.ai

AD cross-model-knowledge-extraction

跨模型蒸馏工程化的第一环:从 WorkBuddy 内部教师技能的 SKILL.md(或任意技能正文) 中结构化提取能力签名——工作流步骤、触发场景、已知限制/坑、工具脚本、以及可被 蒸馏的决策规则(if/when-then/必须)。输出 JSON 能力画像,直接喂给 model-distillation 的签名合成与对抗验证。纯标准库、零依赖、可本地实跑(--selftest 自带样例)。

ClawHub Agent Skills author: qq435912743 v1.0.0 MIT-0 6 files body ≈ 549 tokens Open the sourceclawhub.ai analyzed 2 d ago

跨模型蒸馏工程化的第一环:从 WorkBuddy 内部教师技能的 SKILL.md(或任意技能正文) 中结构化提取能力签名——工作流步骤、触发场景、已知限制/坑、工具脚本、以及可被 蒸馏的决策规则(if/when-then/必须)。输出 JSON 能力画像,直接喂给 model-distillation…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "agent_created"
    • note frontmatter-key unknown frontmatter key "visibility"

    Process rating: all ten parameters 46/100

    • 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
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 17 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 549 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +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
    • +3Description length 196: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (3 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill’s extractor is local and understandable, but it adds persistent learning, user preference storage, and instructions to write experience back into the skill without enough scoping or consent.
    LLM: suspicious (high) · 14 Aug 2026