SKILLEMALL.ai

AB magpie

Query A-share (Chinese stock market) quotes, fund flows, K-lines, watchlist, alert rules, and 龙虎榜 via the local magpie daemon. Use when the user asks about a stock by code or name, wants to set/list/remove price alerts, asks for today's resource fund flow, requests a morning/evening/weekly portfolio digest, queries 龙虎榜 (top billboard), or asks "what's <stock> doing now". DO NOT use for US stocks, HK stocks, crypto, technical analysis (MA/MACD), order execution, or news/sentiment — magpie is v1 A-share monitoring only.

ClawHub Agent Skills author: SymbolStar v0.0.4 MIT-0 2 files body ≈ 1 991 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 76/100 · Nearly there — weak spots: inputs and preconditions

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
B
76/100
Nearly there
Inputs and preconditions w 11
0
Tools and files w 18
60
Result and completion w 14
60
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 76/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 58 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 8 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1991 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 523: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 58 items
    • +3Output format is stated explicitly
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a coherent local A-share monitoring skill that only documents calls to a localhost daemon, with some normal privacy and state-change cautions.
    LLM: benign (high) · VirusTotal: · 29 May 2026