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BD lota-football

查询足球比赛列表和单场特征报告。世界杯历史比赛免费访问。包含 AI Agent 投注分析提示词（引导词/数据提示词/决策框架/输出格式）。

ClawHub Agent Skills author: KingVergil v2.1.0 MIT-0 6 files · 3 scripts body ≈ 2 085 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceAI and agentsInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
92
Quality 40%
69
Run on models
none yet
Process rating
D
46/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Exfiltration net-credential-use lota_compact_fet.sh:37
    Credential used in a network call (verify the destination is the intended service)
    curl_cmd+=("-H" "X-API-Key: ${API_KEY}")
  • low Exfiltration net-credential-use lota_fetch_future_24h.sh:142
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    [[ -n "$API_KEY" ]] && curl_cmd+=(-H "X-API-Key: $API_KEY")
    quoted
  • low Exfiltration net-credential-use lota_football_matches.sh:50
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    [[ -n "${API_KEY}" ]] && curl_cmd+=("-H" "X-API-Key: ${API_KEY}")
    quoted
  • low Dangerous commands cmd-cron-mention SKILL.md:199
    Mentions editing / listing crontab
    crontab -e

Files scanned: 6. 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")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 100Steps. 37 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2085 tokens
  • 100Running it twice. No mutating operations
  • low 16 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (9 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 69: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (22 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill appears to perform its stated football-data function, but it sends an optional API key over plain HTTP by default, so users should review it before use.
LLM: suspicious (high) · VirusTotal: · 9 Jul 2026