Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ZJU-REAL/Easelnpx agentmods add skills/zju-real/easel/skill-zhihu-answerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zju-real/easel/skill-zhihu-answer)<a href="https://agentmods.dev/skills/zju-real/easel/skill-zhihu-answer"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-zhihu-answer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zju-real/easel/skill-zhihu-answer"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-zhihu-answer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00142 | $0.01992 |
| Opus 5 | $0.00071 | $0.00996 |
| Sonnet 5 | $0.00028 | $0.00398 |
| Haiku 4.5 | $0.00014 | $0.00199 |
Grade A, and why
skill-zhihu-answer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
skill-zhihu-answer(发布层 · 知乎问答回答)
在知乎问答帖子下发布原创回答:搜索热门问题 → 检查可答性 → 调用制作层 SKILL 写内容 → Playwright 发布。 核心脚本:
skills/shared/scripts/zhihu_answer.py(CWD=项目根)。命令速查见references/commands.md。
与其他 SKILL 的区别
| SKILL | 定位 |
|---|---|
| skill-zhihu-answer(本 SKILL) | 知乎问答帖的回答发布:搜题 + 写内容 + 发布 |
| skill-zhihu-publisher | 知乎专栏文章(zhuanlan)发布,非问答回答 |
| skill-cross-platform-publish | 一稿多发,多平台分发 |
| novel-writer / copywriting | 制作层,生产回答正文;本 SKILL 调用它 |
核心流程
1. 搜索热门问题(可选,或用户直接给 URL)
↓
2. 检查可答状态(未答过 + WriteAnswerButton 存在)
↓
3. 制作层写内容(用 novel-writer / copywriting SKILL,或用户自备文本)
↓
4. 发布前人设检查(有 Profile 时)
↓
5. zhihu_answer.py --exec 发布
↓
6. 发布后留痕(persona_gate record + publish-log record)
Step 1:搜索热门问题(可选)
用已登录的 ZhihuProfile 搜索问题,直接访问候选页取真实回答数(搜索结果元数据不准):
page.goto("https://www.zhihu.com/search?type=question&q=<关键词>", wait_until="networkidle")
# 直接访问候选问题页取真实数据
page.goto("<问题URL>", wait_until="domcontentloaded")
import re
m = re.search(r'(\d[\d,]*)\s*个回答', page.inner_text("body"))
ans_count = int(m.group(1).replace(',', '')) if m else 0
zhihu_answer.py目前不含搜索功能,搜索用临时脚本或用户直接给 URL(逻辑见references/commands.md§6)。
Step 2:检查可答状态
has_write = page.locator(".WriteAnswerButton").count() > 0
already_answered = page.evaluate("""
() => Array.from(document.querySelectorAll('button'))
.some(b => (b.innerText||'').trim() === '编辑回答')
""")
can_answer = has_write and not already_answered
⚠️ 每个用户在同一问题只能回答一次。已答的问题显示「编辑回答」而非「写回答」。 对已答问题不要重复发布,否则进入编辑旧答案流程(发布按钮变为「提交修改」)。
Step 3:制作层写内容
回答正文属于制作层,用制作层 SKILL 写(novel-writer 或 copywriting),也可用用户提供的文本。
内容存为 outputs/主题名/answer_<问题ID>.md。
写作要点(恐怖/悬疑题材示例):第一人称、冷静克制、暗示>直白;短段落多换行适配手机; 开篇 500 字内建立世界观 + 第一个恐怖节点;文末加"本故事纯属虚构"。
Step 4:发布前人设检查
cd <项目根> && python skills/shared/scripts/persona_gate.py check --score <评分>
# 始终退出码 0;低于 80 分时告知偏离点,但不阻断用户发布
Step 5:发布命令
# Dry-run 预检(默认,不真正发布)
cd <项目根> && python skills/shared/scripts/zhihu_answer.py \
--question <问题URL> --content-file <回答内容.md>
# 正式发布
cd <项目根> && python skills/shared/scripts/zhihu_answer.py \
--question <问题URL> --content-file <回答内容.md> --exec
# 调试模式(有头浏览器,首次校验选择器时用)
cd <项目根> && python skills/shared/scripts/zhihu_answer.py \
--question <问题URL> --content-file <回答内容.md> --exec --headed
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 188 lines · 142 tokens per session scan A 42ed18a04c01
skill-zhihu-answer is a skill published in the GitHub repository ZJU-REAL/Easel (710 stars, last pushed today), licensed Apache-2.0. It adds 142 tokens to every session and 1,992 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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