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pengdagang1975

天天老师助手

by pengdagang1975 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
326
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0
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1
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Install in OpenClaw
/install tiantian-grader
Description
作业批改专家,支持多份作业连续批改,自动生成班级成绩统计表
Usage Guidance
Before installing, confirm the following: (1) Why does the skill need TENCENT_SECRET_ID and TENCENT_SECRET_KEY? Ask the author which Tencent APIs are used and whether you can provide a scoped service account (minimal permissions) rather than full account keys. (2) The skill writes to /root/.openclaw/workspace and persists a MEMORY.md and uploaded student files — if you will process real student data, ensure you have consent and use a sandbox with limited access and encrypted storage. (3) The SKILL.md uses child_process.exec; this can enable command injection if inputs (filenames, URLs) are not sanitized — request code review or run it in an isolated container. (4) If you cannot review the full code, do not provide high-privilege credentials; instead create a dedicated, least-privilege Tencent account and rotate or revoke keys after testing. (5) Ask the developer for a minimal reproduction that shows explicit Tencent usage (network endpoints, SDK calls) and for documentation of data retention and deletion policies.
Capability Analysis
Type: OpenClaw Skill Name: tiantian-grader Version: 1.0.0 The skill is a homework grading assistant designed to process student assignments, manage rosters, and generate statistical reports. It implements a structured workflow including OCR simulation, manual correction of recognized text, and CSV export of grades. All file operations are restricted to a dedicated workspace directory (/root/.openclaw/workspace/teacher_tiantian), and no evidence of data exfiltration, malicious command execution, or prompt injection was found in skill.md or the handler logic.
Capability Assessment
Purpose & Capability
The skill claims to be a homework-grading assistant which can ingest uploads, grade, and produce reports — that matches many of the file- and report-related operations in SKILL.md. However, the skill declares required environment variables TENCENT_SECRET_ID and TENCENT_SECRET_KEY while the visible code mostly performs local file I/O and uses child_process.exec; there is no obvious, explicit Tencent API usage in the visible snippets to justify granting cloud credentials. Requiring cloud secrets should be explained (e.g., OCR or cloud storage) — otherwise the credential request looks disproportionate.
Instruction Scope
The SKILL.md contains embedded Node.js runtime logic that creates and writes into a workspace under /root/.openclaw/workspace/teacher_tiantian, reads a roster CSV, reads/writes a persistent memory file, saves uploaded files, and uses child_process.exec. These actions read and persist local data and execute shell commands. That scope goes beyond a simple in-memory grading routine: it persists data on disk, manipulates files in a root-owned path, and executes commands — all of which increase risk (data leakage, tampering, command injection) if inputs are not strictly validated.
Install Mechanism
There is no install spec (instruction-only), so no external binaries or archives are fetched during installation. That reduces supply-chain risk. However, the instructions create persistent directories and files under /root/.openclaw/workspace and will write/execute runtime code there, so there is still local persistence risk even without an installer.
Credentials
The skill requires TENCENT_SECRET_ID and TENCENT_SECRET_KEY. A single cloud credential can be reasonable if the skill uses Tencent OCR, storage, or AI services — but the SKILL.md does not clearly show Tencent API calls in the visible parts. Asking for full cloud credentials without explaining the exact APIs/scopes needed is disproportionate. Also the skill requests access to a web-enabled config and a specific model (deepseek-reasoner), expanding its reach.
Persistence & Privilege
always:false (normal). The skill requests session persistence (persist: true) and writes a MEMORY.md and workspace files, so it will leave lasting data on the host. It doesn't claim to change other skills or system-wide config, but persistent storage of uploaded student data and rosters increases sensitivity and should be considered when granting permissions.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install tiantian-grader
  3. After installation, invoke the skill by name or use /tiantian-grader
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of 天天老师助手 (tiantian-grader) for efficient homework grading. - Supports continuous grading of multiple assignments. - Automatically generates class performance statistics. - Includes comprehensive file and roster management. - Offers user-invocable grading actions and detailed result storage.
Metadata
Slug tiantian-grader
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is 天天老师助手?

作业批改专家,支持多份作业连续批改,自动生成班级成绩统计表. It is an AI Agent Skill for Claude Code / OpenClaw, with 326 downloads so far.

How do I install 天天老师助手?

Run "/install tiantian-grader" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is 天天老师助手 free?

Yes, 天天老师助手 is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does 天天老师助手 support?

天天老师助手 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created 天天老师助手?

It is built and maintained by pengdagang1975 (@pengdagang1975); the current version is v1.0.0.

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