Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ntygod/ZhiWei --skill research-assistantgit clone --depth 1 https://github.com/ntygod/ZhiWeiWrote 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/ntygod/zhiwei/research-assistant)<a href="https://agentmods.dev/skills/ntygod/zhiwei/research-assistant"><img src="https://agentmods.dev/badge/skills/ntygod/zhiwei/research-assistant/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/ntygod/zhiwei/research-assistant"><img src="https://agentmods.dev/badge/skills/ntygod/zhiwei/research-assistant.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 | $0.00039 | $0.00660 |
| Opus 5 | $0.00019 | $0.00330 |
| Sonnet 5 | $0.00008 | $0.00132 |
| Haiku 4.5 | $0.00004 | $0.00066 |
Grade A, and why
research-assistant 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 9d 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.
What it actually says
信息调研指南
多源搜索 + 交叉验证 + 结构化整理。核心约束：每条结论都能追溯到来源，矛盾信息必须明示。
适用场景
- 技术选型（框架对比、方案评估）
- 竞品分析 / 市场调研
- 行业动态 / 趋势追踪
- 事实核查（"X 是真的吗 / 数据准吗"）
- 学术文献 / 技术文档检索
- 跨多个来源的对比分析
不适用场景
- 已知答案的简单问题 → 直接回答
- 代码库内搜索 → code-assistant
- 数据集统计 → data-analyst
- 已绑定知识库的精确查询 → 直接
memory
工作流（按调研深度分流）
| 调研深度 | 用户表达 | 路径 |
|---|---|---|
| 快速答 | "X 是什么 / 听说 X 是真的吗" | web_search 1 次 → 直接答（带来源） |
| 深度对比 | "X 和 Y 比 / 选 X 还是 Y / 主流方案有哪些" | 广→深→交叉→结构化 |
| 趋势 / 动态 | "X 最近怎么样 / 行业现在什么趋势" | web_search 限定时间窗 → 多源汇总 |
| 事实核查 | "这个数字对吗 / X 真的做了 Y 吗" | 至少 2 个独立来源验证，矛盾明示 |
各路径要点：
- 广度搜索：
web_search拿全局概览，识别子话题 - 深度抓取：高价值来源用
web_fetch抓正文（不只看搜索摘要） - 交叉验证：关键数据 ≥ 2 个独立来源；冲突时明示分歧而非择一
- 结构化输出：按场景选格式（对比表 / SWOT / 证据链 / 时间线），每条事实带来源
[来源标题](URL) - 保存：长期参考价值的
file_write写报告 +memory(action="create")记关键结论
详细参考
- 搜索命令模板、输出格式表、来源标注规范、错误处理：
{skill_dir}/references/research-workflow.md
What ships with it
1 file 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.
- 9d ago First seen · 60 lines · 39 tokens per session scan A 524966190734
research-assistant is a skill published in the GitHub repository ntygod/ZhiWei (138 stars, last pushed 29d ago), licensed MIT. It adds 39 tokens to every session and 660 once invoked, about $0.0002 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 2026-08-30.
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weekly-review
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mooncite
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