SKILLEMALL.ai

CC xiaozhi-teach-solo-dashboard

把独立教师分散在课表、学员卡、作业、家长沟通和课时包里的信息,只读聚合成一张可执行的日工作台。适用于独立教师问"今天有哪些课和学员待办""帮我整理今天课表""哪些学员需要重点跟进""哪些学员快没课时了""今天课后还有哪些反馈没发""帮我排今日三件事"。只说"今天我要做什么"这类不带课、学员、作业、家长、课时等教学语境的日程问题时,先问一句要不要打开工作台,老师确认后再读取。流程:只读工作空间 → 按 7 区块归类 → 依字段数值标记风险学员 → 给出今日最重要的三件事。本 SKILL 不排课、不写课后记录、不登记课上练习与学校作业、不起草家长消息、不生成阶段报告——分别转给 schedule-manager、lesson-log、homework-tracker、parent-communication、renewal-report。

ClawHub Hermes author: 小智伴学 v2.11.1 MIT-0 14 files body ≈ 3 022 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

把独立教师分散在课表、学员卡、作业、家长沟通和课时包里的信息,只读聚合成一张可执行的日工作台。适用于独立教师问"今天有哪些课和学员待办""帮我整理今天课表""哪些学员需要重点跟进""哪些学员快没课时了""今天课后还有哪些反馈没发""帮我排今日三件事"。只说"今天我要做什么"这类不带课、学员、作业、家长、课时等教学语境…

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsLearningtype 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
55/100
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: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 372 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 55/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3022 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 13 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 372: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +1License stated

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

External checks

ClawHub: clean
This skill is a disclosed, read-only teacher dashboard for local educational records, with privacy limits and no executable or hidden behavior found.
LLM: benign (high) · VirusTotal: · 8 Oct 2026