Explore in MochiBot. Install in chat.Hosted workspaces and MochiBot lightweight setups include the Skills assistant. Choose a Skill and ask for installation in chat. Other OpenClaw setups can follow the first-install guide.
How to use Skills →
MOCHILAB / AI SKILL
Course Grade Policy Scenarios
Use exact decimal/rational calculations for points or weighted groups with explicit missing/excused/ungraded states, drop/replace rules and a declared rounding policy.
Tell your assistant what you want to check and provide the actual relevant materials. It prepares the structured records and asks for facts that affect the result.
Use my syllabus and scores to explain the current weighted grade without treating ungraded work as zero.
What final-exam score would reach my target under these explicit category and drop rules?
You receive a readable report, detailed records and a preserved input snapshot. Use exact decimal/rational calculations for points or weighted groups with explicit missing/excused/ungraded states, drop/replace rules and a declared rounding policy. Recompute category denominators per scenario; solve target score constraints only within supplied bounds and policy.
No official grade certification or transcript prediction. Unsupported policy remains unknown; no default drop/zero/weight renormalization. Explain assumptions accessibly rather than encourage gaming or provide homework answers.
Runs locally with Python 3.10+ standard library; no paid data key or MochiLab backend account is required. Optional extraction and explanation use your current agent model under its existing service terms. No automatic messages, applications, account changes or notifications.