SKILLEMALL.ai

CC xiaozhi-teach-chinese-writing-guide

面向语文老师的作文教学与批改标准工具。当老师说"这周写什么作文"、"作文怎么批改"、"作文讲评怎么上"、"作文怎么定档打分"、"学员的写作风格怎么看"、"写作任务怎么设计"时,建议激活此SKILL。工作流:写作任务设计(命题/半命题/情境)→ 过程引导(构思/起草/修改)→ 等级批改(一至四类文 × 内容/结构/语言/书写)→ 三维观察诊断 → 讲评设计 → 班级写作力记录。只输出批改标准与讲评设计,不代老师逐篇精批、不为学员代写作文。高中按学习任务群设计写作任务(文学写作、思辨写作、实用写作),批改以学业质量水平为骨架。阅读教学转 xiaozhi-teach-chinese-reading-guide;文言文教学转 xiaozhi-teach-chinese-classical-guide。

ClawHub Hermes author: 小智伴学 v2.11.1 MIT-0 18 files body ≈ 3 534 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

面向语文老师的作文教学与批改标准工具。当老师说"这周写什么作文"、"作文怎么批改"、"作文讲评怎么上"、"作文怎么定档打分"、"学员的写作风格怎么看"、"写作任务怎么设计"时,建议激活此SKILL。工作流:写作任务设计(命题/半命题/情境)→ 过程引导(构思/起草/修改)→ 等级批改(一至四类文 ×…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
C
53/100
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

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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 · 0

✓ No critical or high findings

Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 351 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "grade_bands"
  • note frontmatter-key unknown frontmatter key "depends_on"
  • note frontmatter-key unknown frontmatter key "id"
  • note frontmatter-key unknown frontmatter key "min_platform_version"
  • note frontmatter-key unknown frontmatter key "max_round_limit"
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 53/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3534 tokens
  • 100Running it twice. No mutating operations
  • low 14 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 6 example trigger phrases
  • +3Description length 351: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (23 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a Chinese K-12 writing-teaching guide with disclosed student-record workflows and no hidden code, installation script, exfiltration, or unsafe automatic action found.
LLM: benign (high) · VirusTotal: · 8 Oct 2026