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Install in OpenClaw
/install score-query
Description
学分查询技能
Usage Guidance
This skill's code implements a simple local lookup of student scores from a bundled JSON file and does not request secrets or network access, which is low-risk. However the SKILL.md/README declare ffmpeg as a required binary even though the code never uses it — ask the author why ffmpeg is required before installing or running. Recommended actions: (1) Inspect the included files yourself (index.js and database/scores.json) — they are short and readable. (2) If you will run the skill, do so in a sandbox/container if you cannot confirm the ffmpeg requirement. (3) Request clarification or a corrected metadata/manifest from the publisher (remove ffmpeg if unnecessary). (4) Note the minor metadata/version inconsistencies (package.json vs module metadata) as indicators of sloppy packaging; prefer a well-documented source or repo before trusting widely.
Capability Assessment
Purpose & Capability
The skill's name/description and code implement a local student-score query using a bundled JSON file — nothing in the code or README needs ffmpeg. However the SKILL.md/README metadata declares a required binary: ffmpeg. Requiring ffmpeg is unrelated to a score-query skill and is disproportionate/unexplained.
Instruction Scope
The SKILL.md instructions are minimal and the runtime code's behavior is clear: parse the input, read the local database (database/scores.json), and return scores. The instructions/code do not reference other system files, environment variables, network endpoints, or exfiltration.
Install Mechanism
There is no install spec (instruction-only), which limits installation risk. However the package includes code files (index.js and database JSON). No install-time downloads or extract operations are declared. This is low-risk, but the presence of code means users should still review it before running.
Credentials
The skill requests no environment variables, no credentials, and no config paths. That is proportionate to the stated purpose. The only oddity is the declared required binary (ffmpeg) in metadata despite no use of it in code; this does not involve secrets but is an unexplained external dependency.
Persistence & Privilege
The skill does not request persistent/always-on presence (always is false), does not modify other skills or system-wide settings, and only reads its own bundled JSON file. No elevated privileges are requested.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install score-query - After installation, invoke the skill by name or use
/score-query - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.0.2
- Updated to version 0.0.2.
- Added metadata section with description, emoji, and required dependency (ffmpeg).
- No changes to functionality or query modes.
- Improved SKILL.md formatting with OpenClaw metadata.
v0.0.1
Initial release of 学分查询技能:
- Supports querying individual subject scores by student name and subject.
- Allows retrieval of all scores across subjects for a given student.
- Provides conversion from conversational to standard subject names for flexible queries.
Metadata
Frequently Asked Questions
What is 学分查询技能?
学分查询技能. It is an AI Agent Skill for Claude Code / OpenClaw, with 79 downloads so far.
How do I install 学分查询技能?
Run "/install score-query" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 学分查询技能 free?
Yes, 学分查询技能 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 学分查询技能 support?
学分查询技能 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 学分查询技能?
It is built and maintained by bc96 (@bc96); the current version is v0.0.2.
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