Wp Performance Review
elvismdev/claude-wordpress-skills
WordPress performance code review and optimization analysis.
生成月度社媒效果复盘报告，分析小红书、抖音、B站、微博等平台的内容表现，输出下月可执行建议. An agent skill from ZJU-REAL/Easel.
Install Skill Social Performance Review
$ npx skills add ZJU-REAL/Easel --skill skill-social-performance-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ZJU-REAL/Easel skill-social-performance-review --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/ZJU-REAL/Easel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/openclaw/skill-social-performance-review .claude/skills/skill-social-performance-review && 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 "skill-social-performance-review" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-review into .claude/skills/skill-social-performance-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-social-performance-review", 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/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-reviewType 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 ZJU-REAL/Easel --skill skill-social-performance-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ZJU-REAL/Easel skill-social-performance-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/openclaw/skill-social-performance-review .agents/skills/skill-social-performance-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "skill-social-performance-review" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-review into .agents/skills/skill-social-performance-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-social-performance-review", 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 ZJU-REAL/Easel --skill skill-social-performance-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ZJU-REAL/Easel skill-social-performance-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/openclaw/skill-social-performance-review .cursor/skills/skill-social-performance-review && 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 "skill-social-performance-review" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-review into .cursor/skills/skill-social-performance-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-social-performance-review", 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/ZJU-REAL/Easel.git --path skills/openclaw/skill-social-performance-review--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 ZJU-REAL/Easel --skill skill-social-performance-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ZJU-REAL/Easel skill-social-performance-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/openclaw/skill-social-performance-review .gemini/skills/skill-social-performance-review && 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 "skill-social-performance-review" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-review into .gemini/skills/skill-social-performance-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-social-performance-review", 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 ZJU-REAL/Easel skill-social-performance-reviewInstalls 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 ZJU-REAL/Easel --skill skill-social-performance-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/openclaw/skill-social-performance-review .github/skills/skill-social-performance-review && 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 "skill-social-performance-review" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-review into .github/skills/skill-social-performance-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-social-performance-review", 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 ZJU-REAL/Easel --skill skill-social-performance-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ZJU-REAL/Easel skill-social-performance-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/openclaw/skill-social-performance-review .opencode/skills/skill-social-performance-review && 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 "skill-social-performance-review" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-social-performance-review into .opencode/skills/skill-social-performance-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-social-performance-review", 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
skill-social-performance-review- GitHub stars
- 3.4k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 269 words
- Files
- 6 (incl. scripts, references)
- Skills in repo
- 114
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
生成月度社媒效果复盘报告，分析小红书、抖音、B站、微博等平台的内容表现，输出下月可执行建议. An agent skill from ZJU-REAL/Easel.
- Works in 3 steps: 报告：按 references/report-template.md 模板输出到… → 更新上下文 → 交接提示：告知用户如何用复盘结果驱动下月排期
- Tasks that involve Performance reviews
- SKILL.md covers 数据层定位, 输入, 输出 and 数据质量, plus 3 more sections
- Runs Python scripts from its folder; calls python3
What it does
Skill Social Performance Review is an agent skill from ZJU-REAL/Easel. 生成月度社媒效果复盘报告，分析小红书、抖音、B站、微博等平台的内容表现，输出下月可执行建议。 当用户说"月度复盘""效果复盘""这个月表现""内容复盘""运营总结""下月建议""月报"时使用。 和 skill-publish-analytics 的区别：analytics 从发布日志做四维归因，本 SKILL 做跨平台组合级月度复盘。
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `EASEL-META.md`, `references/analysis-framework.md` and `references/benchmarks.md`).
It sits in Business, Finance & HR, covering Performance reviews. The repository describes itself as: An open-source AI agent for social media — discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的… The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Performance reviews
Example prompts
- “/skill-social-performance-review”
Requirements
- Python 3
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- 报告：按 references/report-template.md 模板输出到 outputs/复盘主题/
- 更新上下文
- 交接提示：告知用户如何用复盘结果驱动下月排期
What it can do on your machine
Read from SKILL.md and the folder at commit ede33b8. 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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
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
Skill Social Performance Review loads about 1.2k tokens when it runs, and up to ~4.6k if it reads all its reference files. Until then it costs about 50 tokens; SKILL.md has 269 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); the scripts in this folder are not scanned.
SKILL.md
The full file from ZJU-REAL/Easel at commit ede33b8, republished under its Apache-2.0 licence (© ZJU-REAL). 269 words, ~1,151 tokens.
Download SKILL.mdSave it as
.claude/skills/skill-social-performance-review/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- skill-social-performance-review
- description
- 生成月度社媒效果复盘报告，分析小红书、抖音、B站、微博等平台的内容表现，输出下月可执行建议。 当用户说"月度复盘""效果复盘""这个月表现""内容复盘""运营总结""下月建议""月报"时使用。 和 skill-publish-analytics 的区别：analytics 从发布日志做四维归因，本 SKILL 做跨平台组合级月度复盘。
- layer
- attribute
月度效果复盘
分析上月社媒内容表现，找出有效模式与失败原因，输出客户可读的复盘报告和下月可执行建议。
数据层定位
本 SKILL 是归因链的消费层，不新建数据底座：
- 粉丝 / 时序数据的权威来源是
skill-data-tracker快照底座（outputs/_analytics/snapshots/）；发布事件底座是skill-publish-log（outputs/_analytics/publish-log.json）。有对应底座数据时优先取用做环比与粉丝趋势。 - 本 SKILL 的临时文件与产物不是底座 — 阶段 3 的
outputs/复盘主题/.tmp-{月份}.json是标准化输入（用完即删），context/best-performers.md、context/review-history.md是复盘沉淀，均不重复存储粉丝时序或发布事件本身。 - 当底座数据缺失时，退到 CSV / 截图 / 口述输入（见「数据质量」），不阻断复盘。
输入
用户 prompt 中提供以下信息：
- 复盘月份：哪个月的数据
- 平台：小红书 / 抖音 / B站 / 微博 / 公众号（可多选）
- 数据来源（按优先级）：
- CSV 导出（小红书创作者中心 / 抖音创作者服务平台 / B站创作中心 / 微博数据中心）
- 截图（各平台后台数据概览）
- 口述（用户描述哪些帖子表现好/差）
- 业务背景（可选）：当月是否有特殊事件、促销、付费推广
示例 prompt：
Execute /skill-social-performance-review
月份：2025年6月
平台：小红书
数据：附上后台截图
背景：6月中旬做了一次好物分享合集输出
结构化月度复盘报告，保存到 outputs/复盘主题/[客户名]-social-review-[月份]-[年份].md。
报告包含：月度概览、表现最佳/最差帖子分析、内容支柱与格式拆解、关键洞察、下月建议。
完整报告模板见 references/report-template.md。
数据质量
SKILL 适配三种数据质量等级，缺数据不中断分析：
| 等级 | 数据来源 | 分析深度 |
|---|---|---|
| 完整 | CSV 导出 + 账号概览截图 | 逐帖评分，完整指标对比 |
| 部分 | 截图或 Top/Bottom 帖子列表 | 模式分析，标注数据缺口 |
| 最少 | 用户口述表现好/差的帖子 | 定性分析 + 基于最佳实践的建议 |
在报告开头明确标注数据来源和质量等级。
执行步骤
阶段 0 — 环境准备
读取以下上下文文件（存在则读，不存在则跳过并记录）：
context/brand-style.md— 内容支柱、平台定位、目标context/content-calendar.md— 上月排期计划context/best-performers.md— 历史高表现帖子context/review-history.md— 历史评分趋势outputs/复盘主题/最新文件 — 上月复盘（用于环比）
阶段 1 — 信息收集
收集复盘月份、平台、数据来源、业务背景和当月目标。
若用户未准备导出数据，提供导出步骤指引：
- 小红书：创作者中心 → 数据中心 → 内容分析 → 选时间范围
- 抖音：创作者服务中心 → 数据看板 → 作品分析
- B站：创作中心 → 数据中心 → 稿件分析
- 微博：微博数据中心 → 内容分析
- 公众号：公众号后台 → 统计 → 内容分析
若无法导出，请用户提供：Top 3 帖子 + Bottom 3 帖子 + 粉丝变化 + 意外表现帖子。
阶段 2 — 数据标准化
接受 CSV / 截图 / 口述，统一提取：帖子日期、类型、文案摘要、触达、互动、保存/点击、分享、互动率。
清洗规则：
- 付费推广帖子排除出有机基准，单独标注
- Reels/短视频触达天然膨胀，对比格式时注明
- 发帖空白期单独记录
阶段 3 — 效果分析
先把标准化数据落成 JSON，交给 scripts/review.py 做确定性计算，再由你解读。
不要手算互动率、不要心排 Top/Bottom、不要心算环比和加权评分。
把阶段 2 标准化后的数据写成输入 JSON（outputs/复盘主题/.tmp-{月份}.json）：
{
"month": "2026-06", "platform": "xiaohongshu",
"followers": 5200, "followers_change": 180,
"previous": {"avg_engagement_rate_pct": 4.2, "reach": 42000},
"plan": {"planned_posts": 12},
"benchmark": {"engagement_rate_avg": 0.04},
"posts": [
{"title": "...", "date": "2026-06-05", "type": "轮播", "pillar": "好物",
"reach": 8000, "impressions": null, "views": null,
"likes": 420, "comments": 60, "saves": 300, "shares": 40}
]
}字段可缺（付费推广帖先剔除再入 posts）。互动率基数优先 reach→impressions→views。
previous/plan/benchmark 缺失时对应分析降级，不中断。运行：
python3 skills/openclaw/skill-social-performance-review/scripts/review.py score --input outputs/复盘主题/assets/2026-06.json脚本返回：逐帖互动率与综合分、Top3/Bottom3（小红书按收藏排、其他按互动率排）、
支柱聚合、格式聚合、环比（互动率/触达/粉丝）、加权内部评分及所用维度、warnings。
据脚本结果完成 7 项分析（详见 references/analysis-framework.md）：账号快照 / 最佳帖子 /
最差帖子 / 内容支柱表现 / 格式表现 / 开头分析（脚本不做，需读文案首句）/ 发帖节奏。
基准数据参考 references/benchmarks.md。分析完删除临时 JSON。
阶段 4 — 竞品观察（可选）
仅在有竞品账号且配置了 Playwright/Firecrawl MCP 时执行。 观察竞品上月发帖频率、内容组合、格式偏好和互动水平，提炼 4-6 条对比要点。
无 MCP 工具时跳过并在报告中注明。
阶段 5 — 洞察与建议
- 关键洞察（2-4 条）：连接因果，解释当月表现的核心模式
- 下月建议（3-5 条，按预期影响排序）：每条包含"做什么 / 数据依据 / 如何落地"
- 排期调整：支柱比例、格式组合、开头策略、发帖频率的具体变更建议
建议必须具体可执行 — 不写"多发轮播"，写"轮播从每月 2 条增至 4 条，聚焦[表现最佳支柱]"。
阶段 6 — 输出
- 报告：按
references/report-template.md模板输出到outputs/复盘主题/ - 更新上下文：
context/best-performers.md— 追加本月 Top 3context/review-history.md— 追加一行月度摘要（触达 / 互动率 / 粉丝变化 / 评分）
- 交接提示：告知用户如何用复盘结果驱动下月排期
内部评分
综合评分 1-10 由 scripts/review.py score 的 internal_score 字段确定性给出
（不要自己心算加权），记入 context/review-history.md。维度与权重：
| 维度 | 权重 |
|---|---|
| 互动率 vs 基准 | 25% |
| 粉丝增长趋势 | 20% |
| 最佳帖子表现 | 20% |
| 排期执行率 | 15% |
| 触达趋势 | 20% |
脚本会剔除缺数据的维度并对剩余权重重新归一化，dimensions_used 标明实际参与维度。
注意事项
- 收藏/点赞是小红书最重要指标 — 反映内容被用户认为有价值，优先于曝光量
- 不同平台核心指标不同 — 小红书看收藏，抖音看完播率，B站看硬币/投币，微博看转发
- 缺数据不废复盘 — 基于用户记忆的定性复盘仍有价值，标注局限并推动下月导出
- 付费推广帖子污染有机基准 — 务必确认并排除
- 短视频触达膨胀 — 服务非粉丝，不直接与图文对比触达
- 建议部分是核心 — 创作者最想知道下月该做什么
Profile 感知
- 有 Profile：
- 读取
platform确定分析平台和基准 - 读取内容支柱做支柱级拆解
- 读取品牌风格校验内容一致性
- 读取历史数据路径做环比分析
- 读取
- 无 Profile：
- 询问用户目标平台和当月目标
- 使用
references/benchmarks.md通用基准 - 跳过支柱分析（或让用户口述支柱分类）
- 附注："如提供账号 Profile，可启用支柱拆解和历史趋势分析"
© ZJU-REAL, Apache-2.0. 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 5 other files (scripts, references) in skills/openclaw/skill-social-performance-review of ZJU-REAL/Easel.
- SKILL.md
- EASEL-META.md
- references/analysis-framework.md
- references/benchmarks.md
- references/report-template.md
- scripts/review.py
Open the folder on GitHubat commit ede33b8
Compare with similar skills
Skill Social Performance Review 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 |
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| 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 |
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Questions about Skill Social Performance Review
What does Skill Social Performance Review do?
生成月度社媒效果复盘报告，分析小红书、抖音、B站、微博等平台的内容表现，输出下月可执行建议. An agent skill from ZJU-REAL/Easel. Skill Social Performance Review is an agent skill from ZJU-REAL/Easel.
When should I use Skill Social Performance Review?
Skill Social Performance Review fits situations like: tasks that involve Performance reviews.
How do I install Skill Social Performance Review in Claude Code?
Run `npx skills add ZJU-REAL/Easel --skill skill-social-performance-review -a claude-code`. Or copy the skill folder (skills/openclaw/skill-social-performance-review in ZJU-REAL/Easel) into .claude/skills/skill-social-performance-review in your project. Claude Code loads it when a task matches its description.
How do I install Skill Social Performance Review in Codex?
Run `npx skills add ZJU-REAL/Easel --skill skill-social-performance-review -a codex`. Or copy the skill folder (skills/openclaw/skill-social-performance-review in ZJU-REAL/Easel) into .agents/skills/skill-social-performance-review in your project. Codex loads it when a task matches its description.
Can I use Skill Social Performance Review 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 ZJU-REAL/Easel --skill skill-social-performance-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-social-performance-review, .gemini/skills/skill-social-performance-review, .github/skills/skill-social-performance-review and .opencode/skills/skill-social-performance-review in your project.
What does Skill Social Performance Review need to run?
Going by SKILL.md and its folder, Skill Social Performance Review needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Skill Social Performance Review 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 Skill Social Performance Review 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Skill Social Performance Review use?
Skill Social Performance Review is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Skill Social Performance Review use?
About 1.2k tokens (SKILL.md is roughly 4.6k 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 3.4k tokens, read only when the agent opens those files.
What are the alternatives to Skill Social Performance Review?
Skills that share tags, products or a category with Skill Social Performance Review: 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 Skill Social Performance Review?
ZJU-REAL (a GitHub organization) maintains it in ZJU-REAL/Easel, which has 3,441 GitHub stars. The repository holds 114 skills in this directory. The repository was last updated on October 11, 2026.
Source: ZJU-REAL/Easel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.