SKILLEMALL.ai

AC market-intel

金融市场情报聚合系统:恐慌指数、指数行情、市场要闻、财经日历、加密货币技术分析。Trigger on: 恐慌指数, 恐惧贪婪, fear greed, 行情, 指数, 大盘, 股价, 要闻, 快讯, 财经日历, 宏观事件, NFP, FOMC, CPI, PPI, PMI, LPR, 非农, 美联储, 欧央行, BTC, ETH, TON, 加密货币, 走势分析, 技术分析, 背离, 顶背离, 底背离

ClawHub Agent Skills author: clawto v1.1.0 MIT-0 10 files · 6 scripts body ≈ 344 tokens Open the sourceclawhub.ai analyzed 29 h ago

金融市场情报聚合系统:恐慌指数、指数行情、市场要闻、财经日历、加密货币技术分析。Trigger on: 恐慌指数, 恐惧贪婪, fear greed, 行情, 指数, 大盘, 股价, 要闻, 快讯, 财经日历, 宏观事件, NFP, FOMC, CPI, PPI, PMI, LPR, 非农, 美联储, 欧央行…

As a process C 60/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

Proceduretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
60/100
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: 10. 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 60/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (market-intel) differs from the folder (clawto-market-intel)
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Execution cost. Instruction body is 344 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +4No input/output examples
    • -31 of 6 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 202: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 15 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This skill fetches public market data and news for market summaries, with no evidence of credential theft, persistence, destructive behavior, or hidden data exfiltration.
    LLM: benign (high) · VirusTotal: · 28 May 2026