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CC cifang-fund-data

获取A股场内基金（ETF、LOF）的历史行情、实时行情和收益率排行数据。使用次方量化API（需要API Key）获取基金列表、历史行情、实时行情和场内基金排行数据。当用户需要获取中国场内基金数据、分析ETF/LOF表现、查询基金历史价格、实时行情或进行金融数据分析时，请使用此技能。

ClawHub Agent Skills author: tianyuwu v1.0.1 MIT-0 7 files body ≈ 1 757 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype 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
74/100
safety, quality, tests
Safety 60%
80
Quality 40%
64
Run on models
none yet
Process rating
C
53/100
Has gaps
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 SKILL.md:69
    Credential used in a network call (verify the destination is the intended service)
    curl -H "x-api-key: $CIFANG_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:91
    Credential used in a network call (verify the destination is the intended service)
    curl -H "x-api-key: $CIFANG_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:123
    Credential used in a network call (verify the destination is the intended service)
    curl -H "x-api-key: $CIFANG_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:154
    Credential used in a network call (verify the destination is the intended service)
    curl -H "x-api-key: $CIFANG_API_KEY" \

Files scanned: 7. 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")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "required_env_vars"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 108 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1757 tokens
  • 100Running it twice. No mutating operations
  • low 11 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 141: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 108 items
  • +4Has examples (10 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This skill is a disclosed Cifang Quant fund-data client that uses an API key to fetch ETF/LOF market data, with no hidden persistence or unrelated behavior found.
LLM: benign (high) · VirusTotal: · 29 May 2026