Prompt Template Authoring
nicobailon/pi-prompt-template-model
Write and run custom Pi prompt templates (slash commands) for this extension.
A skill your agent uses when 王建硕 wants to evaluate whether a change to VoiceDrop's 挖矿 system prompt is actually better than the live version — runs the local eval harness (golden fixtures ×…
Install Wjs Evaling Voicedrop Prompts
$ npx skills add jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jianshuo/claude-skills wjs-evaling-voicedrop-prompts --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/jianshuo/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/wjs-evaling-voicedrop-prompts .claude/skills/wjs-evaling-voicedrop-prompts && 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 "wjs-evaling-voicedrop-prompts" agent skill from https://github.com/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-prompts into .claude/skills/wjs-evaling-voicedrop-prompts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wjs-evaling-voicedrop-prompts", 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/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-promptsType 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 jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jianshuo/claude-skills wjs-evaling-voicedrop-prompts --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianshuo/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/wjs-evaling-voicedrop-prompts .agents/skills/wjs-evaling-voicedrop-prompts && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "wjs-evaling-voicedrop-prompts" agent skill from https://github.com/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-prompts into .agents/skills/wjs-evaling-voicedrop-prompts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wjs-evaling-voicedrop-prompts", 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 jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jianshuo/claude-skills wjs-evaling-voicedrop-prompts --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianshuo/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/wjs-evaling-voicedrop-prompts .cursor/skills/wjs-evaling-voicedrop-prompts && 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 "wjs-evaling-voicedrop-prompts" agent skill from https://github.com/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-prompts into .cursor/skills/wjs-evaling-voicedrop-prompts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wjs-evaling-voicedrop-prompts", 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/jianshuo/claude-skills.git --path wjs-evaling-voicedrop-prompts--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 jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jianshuo/claude-skills wjs-evaling-voicedrop-prompts --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianshuo/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/wjs-evaling-voicedrop-prompts .gemini/skills/wjs-evaling-voicedrop-prompts && 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 "wjs-evaling-voicedrop-prompts" agent skill from https://github.com/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-prompts into .gemini/skills/wjs-evaling-voicedrop-prompts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wjs-evaling-voicedrop-prompts", 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 jianshuo/claude-skills wjs-evaling-voicedrop-promptsInstalls 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 jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jianshuo/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/wjs-evaling-voicedrop-prompts .github/skills/wjs-evaling-voicedrop-prompts && 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 "wjs-evaling-voicedrop-prompts" agent skill from https://github.com/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-prompts into .github/skills/wjs-evaling-voicedrop-prompts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wjs-evaling-voicedrop-prompts", 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 jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jianshuo/claude-skills wjs-evaling-voicedrop-prompts --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jianshuo/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/wjs-evaling-voicedrop-prompts .opencode/skills/wjs-evaling-voicedrop-prompts && 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 "wjs-evaling-voicedrop-prompts" agent skill from https://github.com/jianshuo/claude-skills/tree/main/wjs-evaling-voicedrop-prompts into .opencode/skills/wjs-evaling-voicedrop-prompts/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wjs-evaling-voicedrop-prompts", 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
wjs-evaling-voicedrop-prompts- GitHub stars
- 131
- Token cost
- ~475 tokens
- SKILL.md length
- 111 words
- Files
- 2 (incl. references)
- Skills in repo
- 38
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when 王建硕 wants to evaluate whether a change to VoiceDrop's 挖矿 system prompt is actually better than the live version — runs the local eval harness (golden fixtures ×…
- Works in 6 steps: 拿候选 prompt：把候选版 MINE_SYSTEM 文本写到一个临时文件（如… → 跑产出：cd ~/code/jianshuo.dev/agent &&… → 成对盲评：对每条 fixture，dispatch 一个 subagent，喂… → …
- Dispatches blind pairwise judge subagents
- SKILL.md covers 何时用, 流程（按序） and 边界
- Calls node and npm; needs CLAUDE_API_KEY
What it does
Wjs Evaling Voicedrop Prompts is an agent skill from jianshuo/claude-skills. Use when 王建硕 wants to evaluate whether a change to VoiceDrop's 挖矿 system prompt is actually better than the live version — runs the local eval harness (golden fixtures × champion-vs-candidate, same input), dispatches blind pairwise judge subagents, aggregates a win-rate verdict, and on approval promotes the candidate into agent/src/prompts/mine.js. Triggers — "评估 prompt"、"挖矿 prompt 改好了吗"、"eval prompt"、"比一比两版 prompt"、"/wjs-evaling-voicedrop-prompts".
Its SKILL.md is about 480 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/judge-rubric.md`).
It sits in AI & LLM Engineering, covering Prompt engineering, LLM evaluation and Subagents. The repository describes itself as: 13 Claude Code skills for video production (transcribe / translate / dub / multicam / subtitles / reframe) + WeChat publishing. Compatible with Claude Code, OpenAI Codex CLI… The licence is MIT.
When your agent uses it
- Dispatches blind pairwise judge subagents
- Aggregates a win-rate verdict
- On approval promotes the candidate into agent/src/prompts/mine.js
- — 评估 prompt、挖矿 prompt 改好了吗、eval prompt、比一比两版 prompt、/wjs-evaling-voicedrop-prompts
Example prompts
- “评估 prompt”
- “挖矿 prompt 改好了吗”
- “eval prompt”
- “/wjs-evaling-voicedrop-prompts”
Requirements
- A credential in CLAUDE_API_KEY
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- 拿候选 prompt：把候选版 MINE_SYSTEM 文本写到一个临时文件（如 /tmp/cand-prompt.txt）；冠军 = 当前 mine.js 的 MINE_SYSTEM（脚本自动读）。
- 跑产出：cd ~/code/jianshuo.dev/agent && CLAUDE_API_KEY=$CLAUDE_API_KEY node eval/run-eval.mjs /tmp/cand-prompt.txt 。产出落…
- 成对盲评：对每条 fixture，dispatch 一个 subagent，喂 references/judge-rubric.md + 该 fixture 的 transcript + 两份产出。A/B 顺序随机（一半 fixture 把 candidate 放 A、一半放…
- 聚合：把还原后的 verdicts（winner ∈ candidate/champion/tie）+ 候选 proxyFails 喂 aggregate()，渲染 renderReport() → 写 eval/runs//report.md。
- 人工终审：把胜负最接近、分歧最大的 1–2 条产出并排摆给用户。机器只筛掉明显更差的，文风最后一票是用户。
- 晋级：仅当 decision==="promote"（胜率 ≥70% 且无回退）且用户点「认可」——把候选写回 agent/src/prompts/mine.js 的 MINE_SYSTEM，commit（message 附 runId 与胜率），并跑 npm test…
What it can do on your machine
Read from SKILL.md and the folder at commit b2690f5. 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
Shell commands in SKILL.md call:
nodenpm
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
CLAUDE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Wjs Evaling Voicedrop Prompts loads about 475 tokens when it runs, and up to ~739 if it reads all its reference files. Until then it costs about 121 tokens; SKILL.md has 111 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 jianshuo/claude-skills at commit b2690f5, republished under its MIT licence (© jianshuo). 111 words, ~475 tokens.
Download SKILL.mdSave it as
.claude/skills/wjs-evaling-voicedrop-prompts/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- wjs-evaling-voicedrop-prompts
- description
- Use when 王建硕 wants to evaluate whether a change to VoiceDrop's 挖矿 system prompt is actually better than the live version — runs the local eval harness (golden fixtures × champion-vs-candidate, same input), dispatches blind pairwise judge subagents, aggregates a win-rate verdict, and on approval promotes the candidate into agent/src/prompts/mine.js. Triggers — "评估 prompt"、"挖矿 prompt 改好了吗"、"eval prompt"、"比一比两版 prompt"、"/wjs-evaling-voicedrop-prompts".
VoiceDrop 挖矿 prompt 评估
harness = 本 skill（协议）+ jianshuo.dev agent/eval/（脚本/数据）。运行时 = 本地 Claude Code。
被测对象 = agent/src/prompts/mine.js 的 MINE_SYSTEM（git 即版本库）。
何时用
用户改了挖矿 prompt（MINE_SYSTEM），想用数据判断改好了还是改坏了，而不是凭感觉看一两次。
流程（按序）
- 拿候选 prompt：把候选版
MINE_SYSTEM文本写到一个临时文件（如/tmp/cand-prompt.txt）；冠军 = 当前mine.js的MINE_SYSTEM（脚本自动读）。 - 跑产出：
cd ~/code/jianshuo.dev/agent && CLAUDE_API_KEY=$CLAUDE_API_KEY node eval/run-eval.mjs /tmp/cand-prompt.txt <runId>。产出落eval/runs/<runId>/。先看终端有没有「确定性回退」警告——有就先停，多半是候选 prompt 破坏了 JSON 输出。 - 成对盲评：对每条 fixture，dispatch 一个 subagent，喂
references/judge-rubric.md+ 该 fixture 的 transcript + 两份产出。A/B 顺序随机（一半 fixture 把 candidate 放 A、一半放 B，记录映射，收到结果后还原成 champion/candidate）。裁判模型用与生成（opus）不同家族的模型。收每条的{winner, dims, reason}。 - 聚合：把还原后的
verdicts（winner ∈ candidate/champion/tie）+ 候选 proxyFails 喂aggregate()，渲染renderReport()→ 写eval/runs/<runId>/report.md。 - 人工终审：把胜负最接近、分歧最大的 1–2 条产出并排摆给用户。机器只筛掉明显更差的，文风最后一票是用户。
- 晋级：仅当
decision==="promote"（胜率 ≥70% 且无回退）且用户点「认可」——把候选写回agent/src/prompts/mine.js的MINE_SYSTEM，commit（message 附 runId 与胜率），并跑npm test确认没破坏。否则保留报告、不动生产版。
边界
- 只评挖矿 prompt（
MINE_SYSTEM/MINE_SYSTEM_FORCE）。审核/语音编辑 prompt 是不同 eval 模式，不在本 skill。 - 不测成本/缓存/延迟（本地缓存行为≠生产）；不做无人值守。
- 真实金标集要 ≥10 条才可信（见
agent/eval/fixtures/README.md的补充流程）；种子 2 条只够自测流程。
© jianshuo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (references) in wjs-evaling-voicedrop-prompts of jianshuo/claude-skills.
- SKILL.md
- references/judge-rubric.md
Open the folder on GitHubat commit b2690f5
Compare with similar skills
Wjs Evaling Voicedrop Prompts 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 |
|---|---|---|---|---|---|---|
| Wjs Evaling Voicedrop Prompts this skilljianshuo/claude-skills | 131 | — | ~475 | Automated safety check: Pass | MIT | |
| Prompt Template Authoringnicobailon/pi-prompt-template-model | 321 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Context Auditundefined-ui/second-brain-os | 1k | — | ~802 | Automated safety check: Pass | MIT | |
| AI Product Managementandreaskelm/pm-brain | 234 | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| LLM-as-Judge Prompt Writerai-evals-course/evals-skills | 1.5k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Analyze Runget-convex/convex-evals | 130 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Wjs Evaling Voicedrop Prompts
What does Wjs Evaling Voicedrop Prompts do?
A skill your agent uses when 王建硕 wants to evaluate whether a change to VoiceDrop's 挖矿 system prompt is actually better than the live version — runs the local eval harness (golden fixtures ×…. Wjs Evaling Voicedrop Prompts is an agent skill from jianshuo/claude-skills.js.
When should I use Wjs Evaling Voicedrop Prompts?
Wjs Evaling Voicedrop Prompts fits situations like: dispatches blind pairwise judge subagents; aggregates a win-rate verdict; on approval promotes the candidate into agent/src/prompts/mine.js; — 评估 prompt、挖矿 prompt 改好了吗、eval prompt、比一比两版 prompt、/wjs-evaling-voicedrop-prompts.
How do I install Wjs Evaling Voicedrop Prompts in Claude Code?
Run `npx skills add jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a claude-code`. Or copy the skill folder (wjs-evaling-voicedrop-prompts in jianshuo/claude-skills) into .claude/skills/wjs-evaling-voicedrop-prompts in your project. Claude Code loads it when a task matches its description.
How do I install Wjs Evaling Voicedrop Prompts in Codex?
Run `npx skills add jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a codex`. Or copy the skill folder (wjs-evaling-voicedrop-prompts in jianshuo/claude-skills) into .agents/skills/wjs-evaling-voicedrop-prompts in your project. Codex loads it when a task matches its description.
Can I use Wjs Evaling Voicedrop Prompts 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 jianshuo/claude-skills --skill wjs-evaling-voicedrop-prompts -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wjs-evaling-voicedrop-prompts, .gemini/skills/wjs-evaling-voicedrop-prompts, .github/skills/wjs-evaling-voicedrop-prompts and .opencode/skills/wjs-evaling-voicedrop-prompts in your project.
What does Wjs Evaling Voicedrop Prompts need to run?
Going by SKILL.md and its folder, Wjs Evaling Voicedrop Prompts needs the command-line tools its instructions call (node and npm) and credentials named CLAUDE_API_KEY. Our summary lists: A credential in CLAUDE_API_KEY.
Does Wjs Evaling Voicedrop Prompts access the network?
SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Wjs Evaling Voicedrop Prompts 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 Wjs Evaling Voicedrop Prompts use?
Wjs Evaling Voicedrop Prompts 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 Wjs Evaling Voicedrop Prompts use?
About 475 tokens (SKILL.md is roughly 1.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 264 tokens, read only when the agent opens those files.
What are the alternatives to Wjs Evaling Voicedrop Prompts?
Skills that share tags, products or a category with Wjs Evaling Voicedrop Prompts: Prompt Template Authoring (nicobailon/pi-prompt-template-model, 321 stars), Context Audit (undefined-ui/second-brain-os, 1k stars), AI Product Management (andreaskelm/pm-brain, 234 stars) and LLM-as-Judge Prompt Writer (ai-evals-course/evals-skills, 1.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Wjs Evaling Voicedrop Prompts?
jianshuo (a GitHub user) maintains it in jianshuo/claude-skills, which has 131 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on August 20, 2026.
Source: jianshuo/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.