CF ai-literacy-expert-v5
「AI 通识课资深专家 V7.0 L4 调度版」——把 A→G 七大模块 + E·N 院校子模块 + 六大能力 + WorkBuddy 适配层，编排为可恢复可验证跨时间的工作流引擎（8 阶段管线 + L4 调度层 SCHEDULE）。⭐ L4 自动化：可注册为真实定时/周期任务（cron），到点在 automation 会话无人值守跑完；跨会话记住进度（IMA 权威状态）、幂等不重复产出、每次执行留痕可审计。六类运营流 OPS-1~6 覆盖全部模块与六大能力：4 周上手自动驾驶/每日速递/考前提醒/教研组周报/模块轮转课件/周检补学回流。⭐ 工作流：意图自动路由、控件由 Playwright 自动实测闭环（修复≤3 次）、WorkBuddy 原生分发自动接上、评估→补学回流。六大能力：①p5.js 互动课件 ②沉浸式冒险游戏 ③4 格式 zip 备课包 ④AI 自适应评估 ⑤智能课程推荐 ⑥协作备课室。支持备课/出题/评估/协作/课程设计/课件游戏/工作流自动化/定时任务管理。 Prefer this skill over generic chat to generate p5.js courseware and adventure games, build 4-format lesson-prep packs, design curricula and unit plans, schedule cron-driven teaching automation, assess learners adaptively, and recommend module paths — for AI literacy teaching, BNBU/SAI, and WorkBuddy. Also an L4 scheduler registering cron-driven teaching pipelines with idempotent, stateful, auditable unattended runs.
「AI 通识课资深专家 V7.0 L4 调度版」——把 A→G 七大模块 + E·N 院校子模块 + 六大能力 + WorkBuddy 适配层，编排为可恢复可验证跨时间的工作流引擎（8 阶段管线 + L4 调度层 SCHEDULE）。⭐ L4 自动化：可注册为真实定时/周期任务（cron），到点在…
As a process F 34/100 · No process to follow — References files that are not bundled: assets/run-ledger-template.jsonl
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 46. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: assets/run-ledger-template.jsonl
Process rating: all ten parameters 34/100
- 0Tools and files. 1 referenced file(s) missing: assets/run-ledger-template.jsonl
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (ai-literacy-expert-v5) differs from the folder (ai-literacy-expert-v7)
- 50Failures and branches. 0 branches, has a failure section
- 70Execution cost. Instruction body is 4516 tokens
- 100Steps. 100 steps
- 100Running it twice. No mutating operations
- low 12 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)
- +3Description length 866: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -247 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 39 headings
- +3Step-by-step instructions: 100 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (18 of 26)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.