SKILLEMALL.ai

AC ashare

Use AKShare to answer Chinese market-data questions about A-shares, China indexes, open-end mutual funds, macro indicators, macro calendar events, and finance news flashes. Trigger on requests such as A股行情, 个股价格, 历史K线, 指数走势, 基金净值, 宏观数据, 财联社快讯, market overview, stock quote, fund NAV, macro calendar, or news flash. Prefer this skill when OpenClaw needs structured market data from AKShare instead of free-form web browsing.

ClawHub Agent Skills author: Nick deep234 v1.0.0 MIT-0 4 files body ≈ 882 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, progress reporting

ProcedurePersonal productivityInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
C
61/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
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

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 61/100

    • 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
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 53 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 882 tokens
    • 100Running it twice. No mutating operations
    • low The response is described with custom markup (7 tags): a typed call is more reliable

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 423: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 53 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    The artifacts appear purpose-aligned and disclosed, with no evidence of hidden collection, destructive behavior, or deceptive execution.
    LLM: benign (high) · VirusTotal: · 29 May 2026