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AC wjx-cli-use

Guide for using wjx-cli (Wenjuanxing CLI) to create surveys, query responses, and analyze data. Use when the user mentions: 问卷, 调查, 收集, 表单, 投票, 考试, 测评, 满意度, NPS, 问卷星, wjx, survey, questionnaire, or wants to create surveys, view responses, export data, analyze NPS/CSAT, or manage contacts, departments, and sub-accounts.

ClawHub Agent Skills author: orzwq v0.4.2 MIT-0 12 files · 2 scripts body ≈ 3 546 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationInfrastructuretype 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
A
90/100
safety, quality, tests
Safety 60%
93
Quality 40%
85
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.

Dangerous commands 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 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

    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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • medium Dangerous commands cmd-pipe-to-shell-known-host references/install-nodejs.md:20
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
    • low Dangerous commands cmd-pipe-to-shell setup.sh:190
      Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition; string literal in code, not executed)
      echo "  CentOS:   curl -fsSL https://rpm.nodesource.com/setup_20.x | sudo bash - && sudo yum install -y nodejs"
      detectorcode literal
    • low Dangerous commands cmd-privilege setup.sh:190
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      echo "  CentOS:   curl -fsSL https://rpm.nodesource.com/setup_20.x | sudo bash - && sudo yum install -y nodejs"
      detectorcode literal

    Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "display_name"
    • note frontmatter-key unknown frontmatter key "display_name_en"
    • note frontmatter-key unknown frontmatter key "displayName"
    • note frontmatter-key unknown frontmatter key "name_en"
    • note frontmatter-key unknown frontmatter key "description_zh"
    • note frontmatter-key unknown frontmatter key "description_en"

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 25 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 47 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3546 tokens
    • low The response is described with custom markup (12 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 320: enough signal without eating the budget
    • +4Structure: 29 headings
    • +3Step-by-step instructions: 47 items
    • +4Has examples (13 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)

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

    External checks

    ClawHub: suspicious
    This is a real Wenjuanxing CLI helper, but it can install software, store API keys, and modify or delete live survey/account data without enough explicit safety gates.
    LLM: suspicious (high) · 4 Sept 2026