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BD builtin-tools

跨平台基础工具集 — 16 个独立可组合的 Python 脚本，替代 Agent 平台缺失的基础工具能力。 文件系统（浏览/搜索/读写/替换/删除）、内容搜索（正则）、网络（搜索/抓取/预览）、 运行时安装、持久化记忆、定时任务、任务管理。 纯 Python 标准库，零外部依赖，跨 Windows/macOS/Linux。 自举设计：execute_command.py 可调度所有其他脚本，平台只需支持一条 Python 命令即可全量使用。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 19 files body ≈ 898 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceSoftware 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
86/100
safety, quality, tests
Safety 60%
94
Quality 40%
74
Run on models
none yet
Process rating
D
45/100
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.

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-persistence scripts/automation_update.py:119
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    f'schtasks /create /tn "builtin-tools/{auto_id}" '
    code literal
  • low Dangerous commands cmd-cron-mention scripts/automation_update.py:127
    Mentions editing / listing crontab (string literal in code, not executed)
    return f'# 添加到 crontab: crontab -e\n# {parse_rrule(schedule)}\n# {prompt}'
    code literal

Files scanned: 19. 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 45/100

  • 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
  • 30Running it twice. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 10 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 898 tokens
  • 100Progress reporting. Reports progress

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
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 222: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 10 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 16 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This is a disclosed utility bundle, but it gives an agent broad shell, file, network, install, memory, and automation powers without enough built-in limits or confirmations.
LLM: suspicious (high) · VirusTotal: · 29 May 2026