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AC headteacher-workbench

Bootstrap and operate an AI-native headteacher workspace. Guide users through backend selection, environment-aware Feishu Base access routing, schema installation, data operations, and artifact generation. Use for class management setup, OpenClaw Feishu plugin onboarding, Feishu CLI onboarding, student records, grades, conduct logs, parent communication, schedules, and Word/Excel/PPT outputs. | 搭建并运行班主任 AI Native 工作台：引导用户选择后端、按运行环境路由飞书多维表格接入方式、初始化班级数据库、持续处理学生信息、成绩、德育、家校沟通与文件生成。

ClawHub Agent Skills author: LeyuDame2 v2.1.0 MIT-0 26 files body ≈ 2 301 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

IntegrationSoftware developmentInfrastructureData and analyticstype 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
A
92/100
safety, quality, tests
Safety 60%
95
Quality 40%
88
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

    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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Read Write Edit Bash

    Files scanned: 26. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (headteacher-workbench) differs from the folder (headteacher)
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 6 branches
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 124 steps
    • 100Execution cost. Instruction body is 2301 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 482: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 124 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (6 of 7)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This skill appears purpose-built for class management, but it needs Review because it handles sensitive student records, cloud Feishu workspaces, and local/account identifiers with incomplete privacy and redaction controls.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026