SKILLEMALL.ai

AD elective

PKU Course Selection (选课网) CLI tool built in Rust. Use this skill when working on the elective crate, debugging elective commands, adding features, or when the user mentions 选课, elective, course selection, auto-enroll, CAPTCHA solving, dual-degree, or elective.pku.edu.cn. Also use when dealing with CAPTCHA recognition backends (utool/ttshitu/yunma), automated course enrollment loops, or elective SSO callback. **NOT for general course schedule / 课表 / 这学期上什么课 questions — use the `treehole` skill (`treehole course`) instead, which gives a unified weekly grid with 主修+辅修+双学位. The `elective show` command only sees one program at a time and easily misses courses from the other program for dual-degree students.**

ClawHub Agent Skills author: wjsoj v1.1.0 MIT-0 2 files body ≈ 601 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationLearningSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
D
48/100
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: 2. 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 48/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (elective) differs from the folder (pku-elective)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 20 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 601 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 714: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This is a coherent PKU course-selection helper, but it gives agents sensitive login and enrollment authority without enough explicit user-control boundaries.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026