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Sample size and power calculation tool for clinical trial practitioners. No local R install needed — a cloud R compute service covers all 49 test types and returns publication-grade SVG figures. Natural-language driven; full reproducible R code is returned by default; default output in Chinese or English per OS language setting (prompt can force-switch). / 为临床试验从业者提供的样本量与检验效能计算工具。本地无需安装 R，直接提供云端 R 计算服务（覆盖 49 种检验，并提供 SVG 出版级别图形）。自然语言驱动，默认回传完整 R 代码；默认按操作系统语言设定输出中文或英文（提示词可强制切换）。

ClawHub Agent Skills author: Wintone Zhang v5.8.0 MIT-0 66 files · 27 scripts body ≈ 5 570 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

Sample size and power calculation tool for clinical trial practitioners.

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ProcedurePowerPointWordData and analyticsAI and agentsSoftware 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
C
80/100
safety, quality, tests
Safety 60%
96
Quality 40%
57
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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
  • low Obfuscation obf-base64-blob adapters/bug_report.py:72
    Long base64-looking blob (detector / deny-list definition)
    "Bg1n…XQs
    detector
  • low Obfuscation obf-base64-blob adapters/coze_token_embedded.py:35
    Long base64-looking blob (quoted — discussed, not commanded)
    "Bg1n…IEU
    quoted
  • low Secrets in code secret-high-entropy-token CHANGELOG.md:66
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    python http-service，用原 appId `wbap…D3C` 覆盖发布，
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:41
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | appId | `wbap…D3C` |
    table

Files scanned: 66. 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")
  • warning body-long SKILL.md body ≈ 5570 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "cn_name"
  • note frontmatter-key unknown frontmatter key "invocable"
  • note frontmatter-key unknown frontmatter key "required_commands"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "permissions"
  • note edit-residue the text marks something as outdated (lines 95, 102): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 59/100

  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 25 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5570 tokens
  • 85Steps. 21 steps, 2 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 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
  • +4No input/output examples
  • -311 of 20 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 480: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 21 items
  • +4Reference files are cited in the instructions (14 of 24)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: suspicious
This is a mostly disclosed cloud sample-size calculator, but it needs review because it sends sensitive trial-design parameters to preapproved cloud services and trusts remote response content too broadly.
LLM: suspicious (high) · 9 Oct 2026