Wp Performance Review
elvismdev/claude-wordpress-skills
WordPress performance code review and optimization analysis.
The post-generation AI-tell audit (AI 味诊断). An agent skill from jtydhr88/music-composition-skills.
Install Mc AI Tell Audit
$ npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jtydhr88/music-composition-skills mc-ai-tell-audit --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jtydhr88/music-composition-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/music-composition/skills/mc-ai-tell-audit .claude/skills/mc-ai-tell-audit && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mc-ai-tell-audit" agent skill from https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-audit into .claude/skills/mc-ai-tell-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mc-ai-tell-audit", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-auditType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jtydhr88/music-composition-skills mc-ai-tell-audit --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jtydhr88/music-composition-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/music-composition/skills/mc-ai-tell-audit .agents/skills/mc-ai-tell-audit && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mc-ai-tell-audit" agent skill from https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-audit into .agents/skills/mc-ai-tell-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mc-ai-tell-audit", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jtydhr88/music-composition-skills mc-ai-tell-audit --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jtydhr88/music-composition-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/music-composition/skills/mc-ai-tell-audit .cursor/skills/mc-ai-tell-audit && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mc-ai-tell-audit" agent skill from https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-audit into .cursor/skills/mc-ai-tell-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mc-ai-tell-audit", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jtydhr88/music-composition-skills.git --path plugins/music-composition/skills/mc-ai-tell-audit--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jtydhr88/music-composition-skills mc-ai-tell-audit --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jtydhr88/music-composition-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/music-composition/skills/mc-ai-tell-audit .gemini/skills/mc-ai-tell-audit && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mc-ai-tell-audit" agent skill from https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-audit into .gemini/skills/mc-ai-tell-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mc-ai-tell-audit", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jtydhr88/music-composition-skills mc-ai-tell-auditInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jtydhr88/music-composition-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/music-composition/skills/mc-ai-tell-audit .github/skills/mc-ai-tell-audit && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mc-ai-tell-audit" agent skill from https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-audit into .github/skills/mc-ai-tell-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mc-ai-tell-audit", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jtydhr88/music-composition-skills mc-ai-tell-audit --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jtydhr88/music-composition-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/music-composition/skills/mc-ai-tell-audit .opencode/skills/mc-ai-tell-audit && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mc-ai-tell-audit" agent skill from https://github.com/jtydhr88/music-composition-skills/tree/main/plugins/music-composition/skills/mc-ai-tell-audit into .opencode/skills/mc-ai-tell-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mc-ai-tell-audit", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
mc-ai-tell-audit- GitHub stars
- 154
- Token cost
- ~1.8k tokens
- SKILL.md length
- 481 words
- Files
- 1
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- MIT
At a glance
The post-generation AI-tell audit (AI 味诊断). An agent skill from jtydhr88/music-composition-skills.
- Works in 7 steps: 动笔前必填 → ★ 十四条枚举 → 两个数，不许合并 → …
- A generation comes back and must be accepted
- SKILL.md covers 按任务读哪几节, 边界, 1. 动笔前必填 and 2. ★ 十四条枚举, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Mc AI Tell Audit is an agent skill from jtydhr88/music-composition-skills. The post-generation AI-tell audit (AI 味诊断). Run this on every generated track before accepting it. Covers the fourteen enumerable defaults that generative music models fall into, which of them are machine-measurable and which need ears, why compliance rate and AI-tell count are two separate numbers that must never be merged, the zero-point calibration that sets the pass threshold at 82 rather than 60, the ordered diagnostic path from symptom to owning skill, and the remediation list. Use when a generation comes…
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Performance reviews. The repository describes itself as: Professional agent skills for composing and arranging popular music. The licence is MIT.
When your agent uses it
- A generation comes back and must be accepted
- A track sounds synthetic but you cannot say why
- Deciding whether to accept a take
- A high compliance rate still produced a bad result
Example prompts
- “/mc-ai-tell-audit”
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 7adca0c. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Mc AI Tell Audit loads about 1.8k tokens when it runs. Until then it costs about 189 tokens; SKILL.md has 481 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from jtydhr88/music-composition-skills at commit 7adca0c, republished under its MIT licence (© jtydhr88). 481 words, ~1,822 tokens.
Download SKILL.mdSave it as
.claude/skills/mc-ai-tell-audit/SKILL.md (or your agent's skills folder).- name
- mc-ai-tell-audit
- description
- The post-generation AI-tell audit (AI 味诊断). Run this on every generated track before accepting it. Covers the fourteen enumerable defaults that generative music models fall into, which of them are machine-measurable and which need ears, why compliance rate and AI-tell count are two separate numbers that must never be merged, the zero-point calibration that sets the pass threshold at 82 rather than 60, the ordered diagnostic path from symptom to owning skill, and the remediation list. Use when a generation comes back and must be accepted or rejected, when a track sounds synthetic but you cannot say why, when deciding whether to accept a take, or when a high compliance rate still produced a bad result. AI 味、诊断、验收、听不出来是 AI、照做率、生成后检查。
AI 味诊断（AI-Tell Audit）
生成回来的每一条都要过这个 skill。这是本库的终检。
核心命题：AI 味不是玄学。 生成模型不给规格就走默认值，而这些默认值是可枚举的。 本 skill 就是那份枚举，加上"每一条怎么查、归谁管"。
按任务读哪几节
| 任务 | 读 |
|---|---|
| 刚生成完，要验收 | §2 十四条 → §3 判定 |
| "听着像 AI 但说不出哪里" | §2（★ 逐条查，不要凭直觉） |
| 照做率很高但结果不好 | §4 |
| 要定阈值 | §3.2 零点校准 |
| 查出问题了要改 | §5 整改路径 |
| 人声的四条怎么查 | §6 |
边界
| 不归这里 | 归哪 |
|---|---|
| 规格写完时的检查 | mc-workflow §3.0 的 20 条自查表 |
| 照做率怎么算 | 本 skill §3.1（定义与标定）；honors 三档怎么影响计分见 mc-render-compile §6 |
| 具体怎么改 | 各 L1/L2 skill（§5 给路由） |
| 后端做不到的字段怎么办 | mc-render-compile §6、§7 |
★ 与 20 条自查的分工： 自查问"规格写完没有"，本 skill 问"生成出来的东西像不像人做的"。 两边都看过才算完。 17 条全过的规格照样可能生成出满是 AI 味的音频。
1. 动笔前必填
| 必填 | 问法 |
|---|---|
| ① 这一版的规格与种子 | 没记录就没法复现，审计结果也就没用 |
| ② 后端的 honors 表 | 哪些项是它做不到的——那些不算它的账 |
| ③ 有没有分轨 | 人声四条（§6）需要先分离人声轨 |
2. ★ 十四条枚举
逐条打勾。不要凭整体印象。
| # | AI 味来源（后端默认值） | 对抗的 spec 字段 | 可自动测 | 归谁管 |
|---|---|---|---|---|
| 1 | 段落全是 8 的整数倍 | form[].bars | ✅ 段落边界检测 | mc-arrangement-arch §4 |
| 2 | 能量曲线单调递增，从不减 | energy_curve、subtraction_events | ✅ 分段 RMS | mc-arrangement-arch §2、§3 |
| 3 | 编制从头到尾不变 | roster[].entry/exit | ✅ 分轨 onset 密度 | mc-arrangement-arch §5 |
| 4 | 全曲一个和声循环到底 | bridge 必须离调或转调 | ✅ 和弦识别 | mc-harmony、mc-modulation |
| 5 | fill 刻板落在 4 的倍数 | fill_policy | ✅ onset 峰值位置 | mc-rhythm-section §8 |
| 6 | 没有非人声记忆点 | hooks.arrangement_hook | ⚠️ 半自动（重复段落相似度） | mc-arrangement-arch §7 |
| 7 | 动态压死、频谱质心恒定 | dynamics、width_map | ✅ DR／LRA、质心时序方差 | mc-mix-intent |
| 8 | 网格化、无 push/pull | groove.push_pull | ✅ onset 相对网格偏移 | mc-rhythm-section §3 |
| 9 | 时长永远 3:30，没有尾巴 | target_duration ＋ 结尾处理 | ✅ | mc-arrangement-arch §8 |
| 10 | 每句同样的力度与咬字，没有气声、破音、rubato | vocal.delivery、dynamics_by_section | ⚠️ 需分轨后测短时响度方差 | mc-vocal-direction §2、§4 |
| 11 | 副歌三遍唱得一模一样 | vocal.chorus_variation | ✅ 人声轨分段相似度 | mc-vocal-direction §1④ |
| 12 | 换气点不自然或听不到换气 | vocal.breath_points | ⚠️ 半自动 | mc-vocal-direction |
| 13 | ad-lib 均匀撒或干脆没有 | vocal.ad_libs | ⚠️ 半自动 | mc-vocal-direction |
| 14 | 音准全中 | vocal.pitch_policy | ⚠️ 半自动（分轨后测音高偏移分布） | mc-vocal-direction §4 |
★ 这张表一张三用：本 skill 的骨架、AB 实验评判表的骨架、 以及 20 条自查的来源。改一处要同步三处。
2.1 ★ 三条最容易漏、也最致命的
不是因为它们最难查，而是因为它们不难听——只是"不像人做的"。
| # | 为什么致命 |
|---|---|
| 2（能量只升不降） | 实测 62/62 真实编曲都有下降。这是命中率最高的一条强规则，也是听感上最像 AI 的一条 |
| 8（全部对齐网格） | 实测 62/62。注意读法是"不许全曲每一件都在网格上"——鼓组绝对量化是允许的（→ mc-rhythm-section §2.0） |
| 6（没有非人声记忆点） | 它的症状是"听着还行但记不住"，最容易通过所有其他检查。缺它的歌听完就忘 |
3. 两个数，不许合并
3.1 定义
| 问什么 | 怎么得 | 范围 | |
|---|---|---|---|
| 照做率 | 后端照着规格做了多少 | 逐字段对照规格（仓库内部有度量工具可算成分数） | 0–100 |
| AI 味旗标数 | 成品有多少条机器指纹 | 本 skill §2 逐条打勾 | 0–14 |
★ 绝对不要把它们合成一个分数。 它们诊断的是不同的病：
照做率高 + 旗标少 → 好，接受
照做率高 + 旗标多 → ★ 规格本身写得像 AI（见 §4）
照做率低 + 旗标少 → 后端自己干得不错，但你不可复现（见 §4.2）
照做率低 + 旗标多 → 编译或后端选择有问题，回 mc-render-compile3.2 ★ 零点校准：阈值为什么是 82 不是 60
不相关的、制作精良的成品在照做率表上得 63–66 分。
这是因为任何一首正常的歌都会"碰巧"满足一部分项（有拍速、有段落、有动态）。 所以：
| 线 | 值 |
|---|---|
| 零点（不相关成品） | 63–66 |
| 及格 | 70 |
| 合格 | 82 |
★ 上面三个数是仓库实验的标定值，用来理解量级，不是交付门槛；用户侧没有度量工具时，照做率就是逐字段对照后的一个判断。
★★ 一个踩过的坑：把权重从有区分度的项（boundaries）挪到
没区分度的项（energy_shape，不相关曲目也能拿 0.8），
会抬高所有人的分数，包括零点基线（66→72）。
加权重要加在能区分的项上。
3.3 后端做不到的不算它的账
honors: none 的字段排除计分，不是给 0 分。
详见 mc-render-compile §6.1——这是一个正确性问题，不是口径问题。
4. ★ 照做率高但仍然像 AI
这是本 skill 存在的主要理由。
照做率只衡量"后端有没有照做"，不衡量"规格本身好不好"。 规格写得像 AI，后端忠实执行，结果就是一首照做率 95 的 AI 歌。
Show full SKILL.md (201 more words)Show less
4.1 规格像 AI 的四个征兆
| 征兆 | 查哪 |
|---|---|
intent.one_thing 是为了过 lint 填的，念出来不像一句人话 | mc-workflow §1 的 S0 |
reference_pair 的 borrow 写得很泛（"借它的氛围"） | 同上。"只借前奏的空"才叫写了 |
每个段落的 bars 只是为了避开 8 的倍数而选的怪数字 | mc-arrangement-arch §4——非对称要有理由 |
| 用的进行 / 转调命中了套路警戒线且没写理由 | mc-progressions §3、mc-modulation §6 |
★ 共同点：规则被当成了要满足的条件，而不是要做的选择。 这正好是 AI 味的定义——没有人做过选择。
4.2 照做率低但好听
说明后端自己发挥得不错。可以接受这个成品，但要意识到：
- 你不可复现它
- 你不知道是哪个决定让它好
- 下一首得从头碰运气
★ 处理办法：把这个成品逐字段反推成一份实测 ARR-SPEC（仓库内部有工具可自动测）， 看它和你原本的规格差在哪。那个差值就是你学到的东西。
5. 整改路径
按这个顺序，不要凭直觉跳。
听着"像 AI"
└─ ① 逐字段对照规格，拿照做率
└─ ② 逐条过 §2 的十四条，数出旗标数
├─ 照做率低 → 查 honors
│ ├─ 这个字段该后端是 none → 不是它的错。换后端（YuE2 控制力最强）或接受
│ └─ 不是 none → 编译问题 → mc-render-compile §3
└─ 照做率高但旗标多 → ★ 规格本身的问题 → §4.15.1 症状 → skill（速查）
| 症状 | 先查 |
|---|---|
| 平、没起伏 | mc-arrangement-arch §2 |
| 糊、浑 | mc-texture-layering §4（★ 先查持续音，不是先怪鼓） |
| 主角不突出 | mc-texture-layering §3 四条深度线索 |
| 机械、太准 | mc-rhythm-section §2 ＋ mc-vocal-direction §4 |
| 听着还行但记不住 | mc-arrangement-arch §7（arrangement_hook 是不是空的） |
| 第二遍副歌和第一遍一样 | mc-arrangement-arch §6 ＋ mc-vocal-direction §1④ |
| 人声埋在伴奏里 | 先查音准（mc-vocal-direction §4.1），再查频段 |
| 贝斯在手机上消失 | mc-sound-design §6 差音 |
| 结尾突兀 / 淡出了事 | mc-arrangement-arch §8；★ 检查 exclude 里有没有排除 fade out ending |
| 技术上干净但情绪不对 | mc-mix-intent §3.1（mood 是不是没写） |
| 和声一个循环到底 | mc-harmony §7、mc-modulation |
6. 人声四条（#10、#12、#13、#14）
这四条都需要先把人声轨分离出来。
6.1 分轨
用任何分轨工具把人声轨分出来即可（demucs 一类，或用户生成载体自带的分轨，通常分成人声/贝斯/鼓/其余）。 本 skill 不预设哪一个。
★ 这是分轨在本库里少数必要的场合之一： 多轨语料（Cambridge-MT）给不了"Suno 唱出来的人声"，只能从生成结果里分。
6.2 分轨之后测什么
| # | 测什么 | 判据 |
|---|---|---|
| 10 力度 | 人声轨的短时响度方差 | 方差接近 0 = 全程一个力度 |
| 11 副歌雷同 | 各遍副歌人声轨的分段相似度 | 相似度过高 = 原样复制 |
| 12 换气 | 句间的低能量段 | ⚠️ 半自动，目前靠听 |
| 13 ad-lib | 装饰性发声的分布 | ⚠️ 半自动。均匀 = 撒的，不是唱的 |
| 14 音准 | 音高偏移的分布 | ⚠️ 半自动。全部落在 ±5 音分内 = 修过头/生成的 |
6.3 ⚠ 现状
#12、#13、#14 靠人工听，这是刻意的选择，不是漏了一步。
这三条测的是换气的能量谷、装饰音的分布、音高偏移的分布，它们的自动判据都要按生成模型分别标定阈值，不同模型的基线差得远，硬套一个统一数字容易把唱得好的判成有问题。人工听一遍这三条本来就很快，也正是耳朵天然比机器灵的地方，不算额外负担。
7. 验收清单
每一条生成结果都要过。
- 记录了规格版本与种子
- 逐字段对照过规格，照做率心里有数
- 逐条过了 §2 的十四条，数出了旗标数（不是凭印象）
-
honors: none的项被排除计分，不是给 0 - 照做率高但旗标多的话，查过 §4.1 的四个征兆
- 人声四条至少人工听过一遍
- ★ 耳朵是最后介入的：A/B 打乱 → 成对比较 → 同一对听两遍看结论稳不稳
- 结论两遍不一致 → 这个差异不存在，别改
附：来源
- 骨架来自 本库架构文档 §1.2（十四条枚举表）
- 实测数据来自 仓库实验记录「规则佐证第一轮」 （Cambridge-MT 多轨 62 首自然抽样）
- 仓库内部有度量工具（lint、音频分析、照做率、语料反推），不随插件发布；本 skill 的十四条全部可以人工判
- 十四条里 1–5、7–9、11 在仓库里可机器算，6、10、12、13、14 是人工项
★ 一条方法论提醒（踩过的坑）： 指标测不准时，不要拿指标去推翻教科书，先问指标测的是不是那回事。 例：「最高潮前应有能量回落」在全量 62 首里只有 22%，但在 7 首人工标注真值里是 5/7—— 差距来自算法用能量峰值定位"最高潮"，而人耳不是。 22% 那个数测的不是这条规则。
© jtydhr88, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in plugins/music-composition/skills/mc-ai-tell-audit of jtydhr88/music-composition-skills.
Open the folder on GitHubat commit 7adca0c
Compare with similar skills
Mc AI Tell Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mc AI Tell Audit this skilljtydhr88/music-composition-skills | 154 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Wp Performance Reviewelvismdev/claude-wordpress-skills | 235 | 1 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Align Humanagentscope-ai/OpenJudge | 871 | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Run Mv Hoi Reconstructionnvidia-isaac/video_to_data | 861 | — | ~1.5k | Automated safety check: Pass | Custom licence | |
| Company Analysiszhu1090093659/dsh-trading | 238 | — | ~4.2k | Automated safety check: Pass | Custom licence | |
| Windbg Diagnostic Methodmicrosoft/win-dev-skills | 466 | — | ~1.9k | Automated safety check: Pass | MIT |
Similar skills
Align Human
agentscope-ai/OpenJudge
A skill your agent uses when the user has a judge/grader and human-labeled data, and wants to measure how well the judge agrees with humans, detect systematic biases, determine whether automatic…
Run Mv Hoi Reconstruction
nvidia-isaac/video_to_data
Run and validate the repository-local multi-view camera calibration and human-object reconstruction pipelines.
Company Analysis
zhu1090093659/dsh-trading
A skill your agent uses when the user wants to analyze a listed company, stock, business, or investment target; challenge or revise an existing company report; compare A/H or primary-listing/ADR…
- Official
Windbg Diagnostic Method
microsoft/win-dev-skills
Use with every WinDbg plugin investigation to apply evidence-first reasoning, confidence calibration, contrarian review, structured reporting, and deterministic validation.
AI Index
mizchi/skills
Method and tooling for measuring how AI-generated a piece of prose reads, in Japanese or English.
More from jtydhr88/music-composition-skills
All 29 skills in this repoMc Arrangement Arch
jtydhr88/music-composition-skills
Arrangement architecture (编曲结构学) - the shape of a track over time rather than its notes.
Mc Case Studies
jtydhr88/music-composition-skills
The corpus layer (语料层) - how real recordings are made to testify for or against the textbook rules.
Mc Development
jtydhr88/music-composition-skills
Thematic development (乐思发展层) - what the theme is and what each section does with it.
Mc Form
jtydhr88/music-composition-skills
Song form and section design (曲式与段落) - the terminology, the standard templates, and how to build a setsu backwards from the chorus.
Mc Melody
jtydhr88/music-composition-skills
Melody writing (旋律法) - what a melodic line expresses and how to make it singable.
Mc Progressions
jtydhr88/music-composition-skills
Chord progression lookup library (和弦进行速查库) - the eight famous named progressions with their variants and what each one actually does, a mood reverse-lookup, the eight variation techniques that turn…
Related
Categories
Questions about Mc AI Tell Audit
What does Mc AI Tell Audit do?
The post-generation AI-tell audit (AI 味诊断). An agent skill from jtydhr88/music-composition-skills. Mc AI Tell Audit is an agent skill from jtydhr88/music-composition-skills. The post-generation AI-tell audit (AI 味诊断).
When should I use Mc AI Tell Audit?
Mc AI Tell Audit fits situations like: A generation comes back and must be accepted; A track sounds synthetic but you cannot say why; deciding whether to accept a take; A high compliance rate still produced a bad result.
How do I install Mc AI Tell Audit in Claude Code?
Run `npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a claude-code`. Or copy the skill folder (plugins/music-composition/skills/mc-ai-tell-audit in jtydhr88/music-composition-skills) into .claude/skills/mc-ai-tell-audit in your project. Claude Code loads it when a task matches its description.
How do I install Mc AI Tell Audit in Codex?
Run `npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a codex`. Or copy the skill folder (plugins/music-composition/skills/mc-ai-tell-audit in jtydhr88/music-composition-skills) into .agents/skills/mc-ai-tell-audit in your project. Codex loads it when a task matches its description.
Can I use Mc AI Tell Audit in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jtydhr88/music-composition-skills --skill mc-ai-tell-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mc-ai-tell-audit, .gemini/skills/mc-ai-tell-audit, .github/skills/mc-ai-tell-audit and .opencode/skills/mc-ai-tell-audit in your project.
What does Mc AI Tell Audit need to run?
SKILL.md names no scripts, command-line tools or credentials: Mc AI Tell Audit is instructions for the agent only.
Does Mc AI Tell Audit access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Mc AI Tell Audit safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Mc AI Tell Audit use?
Mc AI Tell Audit is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Mc AI Tell Audit use?
About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Mc AI Tell Audit?
Skills that share tags, products or a category with Mc AI Tell Audit: Wp Performance Review (elvismdev/claude-wordpress-skills, 235 stars), Align Human (agentscope-ai/OpenJudge, 871 stars), Run Mv Hoi Reconstruction (nvidia-isaac/video_to_data, 861 stars) and Company Analysis (zhu1090093659/dsh-trading, 238 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mc AI Tell Audit?
jtydhr88 (a GitHub user) maintains it in jtydhr88/music-composition-skills, which has 154 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on September 22, 2026.
Source: jtydhr88/music-composition-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.