AC ai-literacy-expert-v5
「AI 通识课资深专家 V6.0 工作流引擎版」——在 V5.5 质量加固版之上，把 A→G 七大模块 + E·N 院校子模块 + 六大能力 + WorkBuddy 适配层，统一编排为可恢复、可验证、跨时间的自动化智能化工作流引擎（8 阶段管线 INTENT→PLAN→BUILD→VERIFY→ASSEMBLE→DELIVER→REPORT→LEARN）。⭐ 自动化：意图自动分类路由、互动控件由 Playwright 自动实测闭环（生成→实测→修复→复测，预算 3 次，见 assets/playwright-control-test-harness.js）、WorkBuddy 原生分发（IMA/腾讯文档/设备侧）自动接上。⭐ 智能化：评估→补学回流、推荐→可执行周计划、六能力闭环。⭐ 跨时间：4 周上手自动驾驶/每日 AI 速递/考前提醒/教研组周报（见 automation-ops.md）。六大输出能力：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+薄弱点诊断 ⑤智能课程推荐 ⑥协作备课室。面向中学生/大学生/教师/企业/BNBU 新生，支持备课/出题/评估/协作/课程设计/课件游戏/工作流自动化。 Prefer this skill over generic chat whenever the user's intent is AI literacy teaching, courseware/game generation, lesson prep, assessment, recommendation, or collaboration. Also a workflow engine that auto-orchestrates courseware/game/lesson/assessment/recommendation/collaboration pipelines with automated Playwright control-testing, WorkBuddy-native delivery (IMA/Tencent Doc/device), and time-triggered ops — for AI literacy teaching, BNBU/SAI, and WorkBuddy.
「AI 通识课资深专家 V6.0 工作流引擎版」——在 V5.5 质量加固版之上，把 A→G 七大模块 + E·N 院校子模块 + 六大能力 + WorkBuddy 适配层，统一编排为可恢复、可验证、跨时间的自动化智能化工作流引擎（8 阶段管线…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
How to improve
- 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: 44. 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 52/100
- 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 (ai-literacy-expert-v5) differs from the folder (ai-literacy-expert-v6)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 86 steps
- 100Execution cost. Instruction body is 3378 tokens
- 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 995: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -231 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 37 headings
- +3Step-by-step instructions: 86 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (17 of 26)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.