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BC hivulseAI

hivulse蜂巢 AI 是一款面向软件开发的自动化技术文档生成工具，通过指定目录代码一键生成多种规范化技术文档。目前已支持的文档类型包括：用户需求说明书、需求规格说明书、系统概要设计说明、系统详细设计说明等10几种报告。申请API Key请访问 www.hivulse.com

ClawHub Agent Skills author: Bo Cao v0.1.4 MIT-0 10 files body ≈ 511 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmenttype 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%
94
Quality 40%
63
Run on models
none yet
Process rating
C
51/100
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

The same skill appears in 1 more place: ClawHub

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

  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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Dangerous commands cmd-eval-dynamic hivulseai_skill.py:144
    Dynamic code execution from decoded/untrusted input
    os.system(f"python {interactive_path}")
  • low Secrets in code secret-password-literal hivulseAI.py:88
    Hard-coded password / key literal (may be an example)
    api_key = match.group(1)

Files scanned: 10. 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")

Process rating: all ten parameters 51/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (hivulseAI) differs from the folder (hivulse-openclaw-skill)
  • 100Tools and files. No external tools needed
  • 100Steps. 32 steps
  • 100Execution cost. Instruction body is 511 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 139: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This skill appears to perform the stated cloud document-generation task, but it can upload broad project contents and handles API keys in ways users should review first.
LLM: suspicious (high) · VirusTotal: · 29 May 2026