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BF student-tutor

专为初高中生打造的智能学习导师 Skill。当用户提问学科知识、请求解题辅导、或需要学习指导时触发此技能。支持语文、数学、英语、物理、化学、历史、地理、政治、生物等科目。 功能包括：① 基于课本知识精准回答并给出原文引用；② 提供解题思路引导和关键步骤分析；③ 分析提问语气并给予教师风格的温暖回应。

ClawHub Agent Skills author: whatif146 v1.0.0 MIT-0 10 files body ≈ 1 167 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 31/100 · Will not run — References files that are not bundled: references/textbooks/化学_主册.txt, references/textbooks/化学_增分册.txt, references/textbooks/数学_增分册.txt

ProcedureInfrastructureLearningtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: references/textbooks/化学_主册.txt, references/textbooks/化学_增分册.txt, references/textbooks/数学_增分册.txt
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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. The text references files that are not there: add them or drop the references.
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: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/textbooks/化学_主册.txt
  • warning missing-ref reference to a missing file: references/textbooks/化学_增分册.txt
  • warning missing-ref reference to a missing file: references/textbooks/数学_增分册.txt
  • warning missing-ref reference to a missing file: references/textbooks/物理_增分册.txt
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: references/textbooks/化学_主册.txt, references/textbooks/化学_增分册.txt, references/textbooks/数学_增分册.txt
  • 0Tools and files. 4 referenced file(s) missing: references/textbooks/化学_主册.txt, references/textbooks/化学_增分册.txt, references/textbooks/数学_增分册.txt
  • 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
  • 40Consistency. Frontmatter name (student-tutor) differs from the folder (chinese-student-tutor)
  • 100Steps. 59 steps
  • 100Execution cost. Instruction body is 1167 tokens
  • 100Running it twice. No mutating operations
  • low 10 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
  • +2Single-language instructions
  • +3Description length 150: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 59 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: clean
This is a Markdown-only Chinese tutoring skill with disclosed study-file handling and no evidence of hidden code, credential use, network access, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026