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BD lingxi-ranklist-skill

国泰海通证券-灵犀市场热榜查询skill，支持涨跌幅、成交额、成交量、换手率、当日资金净流入等市场排行榜查询。当用户查询市场榜单时，优先使用本Skill获取数据。触发关键词包括：涨幅榜，跌幅榜，热榜，排行榜，涨幅前10, 资金流向。

ClawHub Agent Skills author: gtht v1.0.1 MIT-0 4 files body ≈ 7 693 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
99
Quality 40%
56
Run on models
none yet
Process rating
D
49/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token skill-entry.js:1
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    var d=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports);var ye=d((Au,Kr)=>{var _e=require("fs"),me=require("path");function Is(){return me.resolve(__dirname,"..")}function vs(){let e=Is(),t=[me.
    detector

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 7693 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "disable"

Process rating: all ten parameters 49/100

  • 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
  • 70Execution cost. Instruction body is 7693 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 261 steps
  • 100Consistency. Name and required fields are in place
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (20 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)
  • +3Description length 116: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -232 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 261 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.

External checks

ClawHub: suspicious
This skill appears purpose-built for market-ranklist queries, but it handles brokerage API credentials in broad local files and makes an unsupported official-publisher claim that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026