BC ct-samplesize
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）。
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
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 5176 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "cn_name" - note
frontmatter-keyunknown frontmatter key "invocable" - note
frontmatter-keyunknown frontmatter key "required_commands" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "triggers" - note
frontmatter-keyunknown frontmatter key "permissions"
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. 18 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 5176 tokens
- 85Steps. 25 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
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
- -35 of 11 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 480: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 25 items
- +4Reference files are cited in the instructions (12 of 21)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.