Ouroboros PM Interview
Q00/ouroboros
Runs a guided product-manager interview that classifies each question automatically and produces a Product Requirements Document.
Agent skill
Sealeap Xiezhi Amazon Scenario Keyword Product Discovery
Discover Amazon product opportunities by extracting scenario, audience, activity, and occasion terms from unusual listings.
Install Sealeap Xiezhi Amazon Scenario Keyword Product Discovery
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-scenario-keyword-product-discovery --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/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery .claude/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery && 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 "sealeap-xiezhi-amazon-scenario-keyword-product-discovery" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery into .claude/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-scenario-keyword-product-discovery", 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/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discoveryType 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 xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-scenario-keyword-product-discovery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery .agents/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sealeap-xiezhi-amazon-scenario-keyword-product-discovery" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery into .agents/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-scenario-keyword-product-discovery", 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 xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-scenario-keyword-product-discovery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery .cursor/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery && 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 "sealeap-xiezhi-amazon-scenario-keyword-product-discovery" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery into .cursor/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-scenario-keyword-product-discovery", 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/xjli360/sealeap-amazon-skills.git --path amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery--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 xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-scenario-keyword-product-discovery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery .gemini/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery && 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 "sealeap-xiezhi-amazon-scenario-keyword-product-discovery" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery into .gemini/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-scenario-keyword-product-discovery", 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 xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-scenario-keyword-product-discoveryInstalls 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 xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery .github/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery && 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 "sealeap-xiezhi-amazon-scenario-keyword-product-discovery" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery into .github/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-scenario-keyword-product-discovery", 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 xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-scenario-keyword-product-discovery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery .opencode/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery && 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 "sealeap-xiezhi-amazon-scenario-keyword-product-discovery" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery into .opencode/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-scenario-keyword-product-discovery", 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
sealeap-xiezhi-amazon-scenario-keyword-product-discovery- GitHub stars
- 251
- Token cost
- ~506 tokens
- SKILL.md length
- 89 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Discover Amazon product opportunities by extracting scenario, audience, activity, and occasion terms from unusual listings.
- Works in 5 steps: 广撒网找特征 → 提取场景词 → 验证词义 → …
- A user has no product inspiration and wants to turn a precise use context into a cross-category candidate set
- SKILL.md covers 目标, 适用任务, 开始前要拿到 and 不可妥协的边界, plus 4 more sections
- Runs Python scripts from its folder
What it does
Sealeap Xiezhi Amazon Scenario Keyword Product Discovery is an agent skill from xjli360/sealeap-amazon-skills. Discover Amazon product opportunities by extracting scenario, audience, activity, and occasion terms from unusual listings. Use when a user has no product inspiration and wants to turn a precise use context into a cross-category candidate set.
Its SKILL.md is about 510 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 `agents/openai.yaml`, `references/mcp-data-plan.md` and `references/playbook.md`).
It sits in Product & Project Management. It works with Model Context Protocol. The repository describes itself as: Reusable Agent Skills for Amazon product research, listings, advertising, inventory, and operations. The licence is MIT.
When your agent uses it
- A user has no product inspiration and wants to turn a precise use context into a cross-category candidate set
Example prompts
- “/sealeap-xiezhi-amazon-scenario-keyword-product-discovery”
Requirements
- Python 3
Workflow steps
5 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 497d4b8. 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.
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
Sealeap Xiezhi Amazon Scenario Keyword Product Discovery loads about 506 tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 89 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 xjli360/sealeap-amazon-skills at commit 497d4b8, republished under its MIT licence (© xjli360). 89 words, ~506 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-xiezhi-amazon-scenario-keyword-product-discovery
- description
- Discover Amazon product opportunities by extracting scenario, audience, activity, and occasion terms from unusual listings. Use when a user has no product inspiration and wants to turn a precise use context into a cross-category candidate set.
Amazon 场景词选品
目标
先找到可搜索的具体场景，再为该场景中的消费者挑选产品，从而把大众商品迁移到更清晰的细分需求。
适用任务
- 从陌生商品标题提取场景入口。
- 用场景词跨类目生成候选。
- 验证场景需求和付费流量盈利可能性。
开始前要拿到
- 目标站点、计划进场窗口和可接受类目。
- 近期上架商品的标题、属性、评论与场景描述。
- 场景词的搜索结果、价格、评论和销量代理数据。
- 目标毛利、供应链与合规限制。
缺少字段时列出证据缺口，并把相关结论标为 FACT、ESTIMATE、ASSUMPTION 或 UNKNOWN；不要补造数据。
不可妥协的边界
- 第三方数据均为估算或代理证据；Amazon 一方报告、后台实时字段和产品事实优先。
- 经验阈值只能作为可调起点，必须展示敏感性分析，不能写成 Amazon 官方规则。
- 不得捏造销量、搜索量、CPC、CVR、成本、认证、产品属性或消费者需求。
- 默认提供诊断或草案。写入前展示对象、旧值、新值、影响、停止线与回退，核对用户已有授权是否覆盖对象、动作与预算；范围已明确授权时继续执行并回读核验，只有未覆盖或扩大的范围才请求批准。
- 不输出或保存素材来源身份、账号、链接、作品编号、互动数据、原始话术或其他可反查来源的线索。
- 不得用不真实场景、虚假适用性或受保护活动标识包装普通产品。
- 找到场景不是立项完成，仍需全链路证据。
工作流
1. 广撒网找特征
浏览近期上架且结构、对象或用途较特殊的商品，目的只是发现不熟悉的语言和场景。
2. 提取场景词
从标题与详情中抽取使用对象、地点、活动、节日和任务词，并翻译为当地消费者真实表达。
3. 验证词义
在前台检查搜索结果是否主要服务同一场景；结果混杂时继续加属性或对象限定。
4. 跨类目扩展
用已验证场景词搜索不同产品形态，再按价格、评论、销量和供应链能力形成候选集。
5. 完成深研
逐个候选验证直接竞品、CPC、CVR、差异化、IP、合规、交期与首批库存。
判断标准
- 场景词必须能指向明确购物任务；仅有流量但结果混杂的词不能作为细分入口。
- 价格约 30 美元以上、评论约 100 以下可作探索条件，但应按品类经济性调整。
- 产品重新定位后必须真实适合该场景，不能只改文案造成误导。
第三方 MCP 数据
需要外部关键词、竞品、评论或公开网页证据时，读取 references/mcp-data-plan.md，并使用 scripts/mcp_research.py。
- 先动态执行
tools/list、search-tools和describe，依据实时inputSchema构造参数。 - 凭证只从环境变量读取，不进入参数、URL、Skill、终端输出或 Git。
- 可能计费的
tools/call先展示 Provider、工具、无密钥参数、预计成本与输出位置，核对已有授权；仅在授权覆盖本次范围时使用--allow-cost，该标志不是费用上限。 - 脱敏结果用
--output写入 Skill 包之外的任务私有目录；不假设安装位置受仓库.gitignore保护。第三方数据标为估算或代理证据。 - 失败一次后记录缺口，不以重复付费重试掩盖不可用状态。
必须交付的结果
- 场景词清单
- 搜索相关性验证
- 跨类目候选池
- 场景—产品—竞品矩阵
- 深研与淘汰结论
结尾列出站点、数据窗口、证据来源、关键假设、缺口、风险、下一步和所有待批准动作。证据不足时写 HOLD，不得包装成可直接执行。
执行细节、证据字段和质量检查见 references/playbook.md。
© xjli360, 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 4 other files (scripts, references) in amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/mcp-data-plan.md
- references/playbook.md
- scripts/mcp_research.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Xiezhi Amazon Scenario Keyword Product Discovery 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 |
|---|---|---|---|---|---|---|
| Sealeap Xiezhi Amazon Scenario Keyword Product Discovery this skillxjli360/sealeap-amazon-skills | 251 | — | ~506 | Automated safety check: Pass | MIT | |
| Ouroboros PM InterviewQ00/ouroboros | 6.2k | — | ~5.7k | Automated safety check: Pass | MIT | |
| Produck Feedback To Buildtryproduck/produck-skills | 511 | — | ~1k | Automated safety check: Pass | Apache-2.0 | |
| Jira Natural Language Interfacejjmartres/opencode | 133 | 3 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Rhesisrhesis-ai/rhesis | 397 | — | ~1.2k | Automated safety check: Pass | Proprietary | |
| Pre Release Testherald-email/herald-mail-app | 146 | — | ~448 | Automated safety check: Pass | Custom licence |
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Questions about Sealeap Xiezhi Amazon Scenario Keyword Product Discovery
What does Sealeap Xiezhi Amazon Scenario Keyword Product Discovery do?
Discover Amazon product opportunities by extracting scenario, audience, activity, and occasion terms from unusual listings. Sealeap Xiezhi Amazon Scenario Keyword Product Discovery is an agent skill from xjli360/sealeap-amazon-skills. Discover Amazon product opportunities by extracting scenario, audience, activity, and occasion terms from unusual listings.
When should I use Sealeap Xiezhi Amazon Scenario Keyword Product Discovery?
Sealeap Xiezhi Amazon Scenario Keyword Product Discovery fits situations like: A user has no product inspiration and wants to turn a precise use context into a cross-category candidate set.
How do I install Sealeap Xiezhi Amazon Scenario Keyword Product Discovery in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a claude-code`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Xiezhi Amazon Scenario Keyword Product Discovery in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a codex`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-scenario-keyword-product-discovery in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery in your project. Codex loads it when a task matches its description.
Can I use Sealeap Xiezhi Amazon Scenario Keyword Product Discovery 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 xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-scenario-keyword-product-discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery, .gemini/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery, .github/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery and .opencode/skills/sealeap-xiezhi-amazon-scenario-keyword-product-discovery in your project.
What does Sealeap Xiezhi Amazon Scenario Keyword Product Discovery need to run?
Going by SKILL.md and its folder, Sealeap Xiezhi Amazon Scenario Keyword Product Discovery needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Xiezhi Amazon Scenario Keyword Product Discovery 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 Sealeap Xiezhi Amazon Scenario Keyword Product Discovery 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 Sealeap Xiezhi Amazon Scenario Keyword Product Discovery use?
Sealeap Xiezhi Amazon Scenario Keyword Product Discovery 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 Sealeap Xiezhi Amazon Scenario Keyword Product Discovery use?
About 506 tokens (SKILL.md is roughly 2k 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 2.3k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Xiezhi Amazon Scenario Keyword Product Discovery?
Skills that share tags, products or a category with Sealeap Xiezhi Amazon Scenario Keyword Product Discovery: Ouroboros PM Interview (Q00/ouroboros, 6.2k stars), Produck Feedback To Build (tryproduck/produck-skills, 511 stars), Jira Natural Language Interface (jjmartres/opencode, 133 stars) and Rhesis (rhesis-ai/rhesis, 397 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Xiezhi Amazon Scenario Keyword Product Discovery?
xjli360 (a GitHub user) maintains it in xjli360/sealeap-amazon-skills, which has 251 GitHub stars. The repository holds 179 skills in this directory. The repository was last updated on September 28, 2026.
Source: xjli360/sealeap-amazon-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.