BD ielts-reading-review
IELTS Reading passage review, scoring, and progress tracking skill. Generates structured review data (JSON) and deploys to www.liuxue.online via saveReview API. The server's review.html template renders JSON into unified pages. No standalone HTML generation needed. Supports batch import of legacy reviews with auto-discovery of review folders. Trigger phrases: 雅思复盘, 帮我复盘阅读, IELTS reading review, 分析错题, 阅读错题分析, 成绩单, 打分, 统计, 进步趋势, 批量导入历史复盘, 历史笔记转 JSON, 把文件夹里的复盘都生成 JSON, 扫一下我电脑里的复盘, 帮我找出所有历史笔记, 自动发现复盘, score, band, progress, batch import, auto scan.
As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Dangerous commands
cmd-shell-rcreferences/CLIENT_MODE_ONBOARDING.md:78Writes to a shell startup file (documentation table row)| `echo $IELTS_USER_TOKEN` 没输出 | `source ~/.zshrc` 或重开终端 |
table
Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7033 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 47/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
- 70Execution cost. Instruction body is 7033 tokens
- 100Steps. 140 steps
- 100Consistency. Name and required fields are in place
- low 15 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
- -2localhost URLs: will not work for another user
- -269 emoji in the instructions: noise for the model
- -31 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 550: enough signal without eating the budget
- +4Structure: 50 headings
- +3Step-by-step instructions: 140 items
- +4Has examples (32 code blocks)
- +4Reference files are cited in the instructions (2 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.