SKILLEMALL.ai

BC xiaozhi-teach-physics-problem-guide

帮初中物理老师把"讲题"升级为系统化的解题教学:五步法(审题→建模→过程分析→列式→求解反思)加变式训练与班级解题档案。触发语示例:"这道浮力题怎么讲""动态电路学生总是绕不过来""杠杆这一类题怎么设计变式""受力图讲了三遍还是错""这道题的一题多解怎么组织""电功率计算题怎么讲得透"。学科判别:题目涉及力、压强、浮力、电路、光学、物态变化等初中物理内容时用本 SKILL;数学运算类讲题转数学学科 SKILL。不处理:整节课的教学设计(转物理教案设计)、实验课的组织与器材(转物理实验教学)、班级测评命题与试卷分析(转老师通用测评 SKILL)。

ClawHub Hermes v2.1.12 16 files body ≈ 2 751 tokens Open the sourceclawhub.ai analyzed 2 d ago

帮初中物理老师把"讲题"升级为系统化的解题教学:五步法(审题→建模→过程分析→列式→求解反思)加变式训练与班级解题档案。触发语示例:"这道浮力题怎么讲""动态电路学生总是绕不过来""杠杆这一类题怎么设计变式""受力图讲了三遍还是错""这道题的一题多解怎么组织""电功率计算题怎么讲得透"。学科判别:题目涉及力、压强、浮…

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
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: 16. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 275 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. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2751 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 275: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (20 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)
  • +1License stated

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

External checks

ClawHub: clean
This is a disclosed middle-school physics teaching skill with scoped class-record features and explicit teacher confirmation and consent checks.
LLM: benign (high) · VirusTotal: