SKILLEMALL.ai

AB junyi-vault-organizer

自动归档 — A two-domain knowledge management system: Business domain (事业域, customizable name, organized by function) and Life & Learning domain (生活学习域, three-layer Inbox→Cognition→Guidebook). Stores to Obsidian vault. Triggers when user mentions 自动归档, 归档, 享育心塾萃取器, 萃取器, or asks to save/store/organize any information — articles, reading notes, class notes, children's words, conversations, ideas, reflections, quotes, or any content they want to keep. Also triggers on save this, remember this, file this away, put this in my notes, store this for later, 记下来, 存一下, 帮我记, 存到知识库.

ClawHub Agent Skills author: XuanranC v2.0.0 MIT-0 4 files body ≈ 3 844 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ReferenceObsidianInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
B
65/100
Nearly there
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: 4. 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
    • 30Running it twice. 9 mutating operations with no state check
    • 70Failures and branches. 4 branches
    • 85Steps. 116 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3844 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 20 top-level sections: this looks like several domains in one skill

    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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -214 emoji in the instructions: noise for the model
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 572: enough signal without eating the budget
    • +4Structure: 45 headings
    • +3Step-by-step instructions: 116 items
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

    External checks

    ClawHub: clean
    This skill is a coherent Obsidian note organizer that writes local text files to a configured vault, with the main risk being accidental persistent saves from broad trigger phrases.
    LLM: benign (high) · VirusTotal: · 29 May 2026