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CF 体彩筛选

中国体育彩票全玩法号码分析、条件筛选、走势图、历史数据查询与数据参考综合工具。 覆盖超级大乐透、排列3、排列5、七星彩、竞彩足球、竞彩篮球、传统足彩全部玩法。 Triggers: "大乐透走势图", "排列三图表", "七星彩数据", "竞彩分析", "体彩号码统计", "历史开奖查询", "杀号定胆", "大乐透和值跨度", "足彩过滤", "后区分析", "冷热号走势", "复式胆拖计算", "大乐透号码", "排列3数据", "体彩遗漏分析", "号码核验", "走势图分析", "复式投注计算", "概率数据", "位置分析", "大小形态", "奇偶形态"

Not recommendedcritical or high security findings
ClawHub Agent Skills author: xljcheng v1.0.0 MIT-0 19 files body ≈ 5 033 tokens Open the sourceclawhub.ai↗ analyzed 20 h ago

中国体育彩票全玩法号码分析、条件筛选、走势图、历史数据查询与数据参考综合工具。 覆盖超级大乐透、排列3、排列5、七星彩、竞彩足球、竞彩篮球、传统足彩全部玩法。 Triggers: "大乐透走势图", "排列三图表", "七星彩数据", "竞彩分析", "体彩号码统计", "历史开奖查询", "杀号定胆"…

As a process F 26/100 · Will not run — References files that are not bundled: references/dlt-rules.md, references/pl3-rules.md, references/pl5-rules.md

IntegrationData and analyticstype 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
C
71/100
safety, quality, tests
Safety 60%
82
Quality 40%
54
Run on models
none yet
Process rating
F
26/100
Will not run
References files that are not bundled: references/dlt-rules.md, references/pl3-rules.md, references/pl5-rules.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  3. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  4. The text references files that are not there: add them or drop the references.
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

  • high Dangerous commands cmd-pipe-to-shell SKILL.md:507
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://skillhub.cn/install/install.sh | bash

Files scanned: 19. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5033 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/dlt-rules.md
  • warning missing-ref reference to a missing file: references/pl3-rules.md
  • warning missing-ref reference to a missing file: references/pl5-rules.md
  • warning missing-ref reference to a missing file: references/qxc-rules.md
  • warning missing-ref reference to a missing file: references/jczq-rules.md
  • warning missing-ref reference to a missing file: references/jclq-rules.md
  • warning missing-ref reference to a missing file: references/terms.md

Process rating: all ten parameters 26/100

Will not run. References files that are not bundled: references/dlt-rules.md, references/pl3-rules.md, references/pl5-rules.md
  • 0Tools and files. 7 referenced file(s) missing: references/dlt-rules.md, references/pl3-rules.md, references/pl5-rules.md
  • 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. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (体彩筛选) differs from the folder (ticai-game-skill)
  • 70Execution cost. Instruction body is 5033 tokens
  • 100Steps. 37 steps
  • low 10 top-level sections: this looks like several domains in one skill

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +3Description length 286: enough signal without eating the budget
  • +4Structure: 76 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (30 code blocks)
  • +3All 13 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

External checks

ClawHub: clean
This skill is a lottery data analysis toolkit with disclosed, user-invoked CSV and optional public-data fetching behavior.
LLM: benign (high) · VirusTotal: · 18 Jul 2026