SKILLEMALL.ai

AC paper-kb

Research paper knowledge base for storing and querying academic papers. Activate when: 1. User shares an arxiv link or PDF file AND expresses intent to save/store it — keywords: "入库"、"存到知识库"、"加到知识库"、"帮我存"、"收藏"、"记录一下"、"保存起来"、"加进去"、"科研知识库" 2. User says something like "帮我加到我的科研知识库" after receiving paper info 3. User queries their personal knowledge base — keywords: "知识库里有没有"、"帮我查一下存过的"、"有没有我之前存的"、"查一下知识库" Do NOT activate when user only wants to summarize, discuss, or analyze a paper without any storage or query intent.

ClawHub Agent Skills author: myd2002 v1.0.2 MIT-0 13 files · 1 script body ≈ 1 831 tokens Open the sourceclawhub.ai analyzed 2 d ago

Research paper knowledge base for storing and querying academic papers.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferencePDFResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
51/100
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: 13. 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 51/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1831 tokens

    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
    • -33 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +3Description length 527: enough signal without eating the budget
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (14 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The skill is a coherent paper knowledge-base integration, but it ships and uses high-impact Gitea admin access and broad remote-storage behavior without enough scoping or safety controls.
    LLM: suspicious (high) · VirusTotal: · 30 May 2026