BC xiaozhi-teach-review-planner
把"从头再讲一遍"变成有间隔、有交叉、有取舍的复习排期。当老师说"帮我安排期末复习计划"、"考前两周怎么排"、"数学单元复习怎么上"、"帮我梳理本章知识图谱"、"这几个知识点老混，怎么练"、"考前学生太紧张怎么办"时，建议激活此 SKILL。工作流：知识图谱 → 重难点 → 阶段策略 → 间隔回看与交叉练习排期 → 复习活动 → 考前状态。本 SKILL 只出复习"计划"，不出复习"作业"：具体题目与分层任务卡转 xiaozhi-teach-assignment-designer，复习卷转 xiaozhi-teach-exam-designer。
把"从头再讲一遍"变成有间隔、有交叉、有取舍的复习排期。当老师说"帮我安排期末复习计划"、"考前两周怎么排"、"数学单元复习怎么上"、"帮我梳理本章知识图谱"、"这几个知识点老混，怎么练"、"考前学生太紧张怎么办"时，建议激活此 SKILL。工作流：知识图谱 → 重难点 → 阶段策略 → 间隔回看与交叉练习排期 →…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 276 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "grade_bands" - note
frontmatter-keyunknown frontmatter key "depends_on" - note
frontmatter-keyunknown frontmatter key "id" - note
frontmatter-keyunknown frontmatter key "min_platform_version" - note
frontmatter-keyunknown frontmatter key "max_round_limit" - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown 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. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3488 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 7 example trigger phrases
- +3Description length 276: enough signal without eating the budget
- +4Structure: 31 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (19 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.