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 agentmods add skills/echovic/boss-skill/tech-researchnpx skills add echoVic/boss-skill --skill tech-researchgit clone --depth 1 https://github.com/echoVic/boss-skillWrote 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/echovic/boss-skill/tech-research)<a href="https://agentmods.dev/skills/echovic/boss-skill/tech-research"><img src="https://agentmods.dev/badge/skills/echovic/boss-skill/tech-research.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00027 | $0.02487 |
| Opus 5 | $0.00014 | $0.01243 |
| Sonnet 5 | $0.00005 | $0.00497 |
| Haiku 4.5 | $0.00003 | $0.00249 |
Grade A, and why
architect/tech-research 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 4d 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
技术调研方法论
适用场景
在进行架构设计和技术选型前,必须先进行系统性的技术调研,了解:
- 业界成熟的技术方案
- 各方案的优缺点和适用场景
- 开源项目的可复用性
- 潜在的技术风险
调研流程
1. 明确调研目标
基于PRD的技术需求,明确需要调研的技术领域:
调研背景模板:
### 1.1 调研背景
**需求概述**:[基于 PRD 的技术需求总结]
**关键技术挑战**:
- [挑战 1]:[具体描述]
- [挑战 2]:[具体描述]
- [挑战 3]:[具体描述]
**调研目标**:
- [ ] 前端框架选型
- [ ] 后端框架选型
- [ ] 数据库选型
- [ ] 缓存方案选型
- [ ] 部署方案选型
2. 使用WebSearch进行调研
搜索策略
通用搜索模式:
"{技术领域} + best practices + 2026"
"{框架名} vs {框架名} comparison 2026"
"{技术领域} + benchmark + 2026"
"best {技术领域} tools 2026"
具体示例:
前端框架调研:
"React vs Vue vs Angular comparison 2026"
"Next.js vs Remix vs Astro 2026"
"best React UI libraries 2026"
后端框架调研:
"Node.js frameworks comparison 2026"
"Express vs Fastify vs Hono benchmark"
"Python web frameworks 2026"
数据库调研:
"PostgreSQL vs MySQL vs MongoDB 2026"
"database for {use case} 2026"
"SQL vs NoSQL when to use"
ORM调研:
"Prisma vs TypeORM vs Drizzle comparison"
"best ORM for {language} 2026"
搜索技巧
- 包含年份:确保获取最新信息
- 对比搜索:使用 "vs" 或 "comparison" 获取对比分析
- 性能搜索:使用 "benchmark" 或 "performance" 获取性能数据
- 实践搜索:使用 "best practices" 获取最佳实践
- 问题搜索:使用 "pros and cons" 或 "disadvantages" 了解缺点
3. 使用WebFetch深入分析
对于重要的技术方案,使用 WebFetch 深入分析官方文档和技术文章:
官方文档:
WebFetch("https://nextjs.org/docs", "总结 Next.js 的核心特性、适用场景和最新版本的主要变化")
WebFetch("https://www.prisma.io/docs", "提取 Prisma 的核心功能、支持的数据库和性能特点")
技术对比文章:
WebFetch("[对比文章URL]", "提取各方案的优缺点对比、性能数据和推荐场景")
GitHub仓库:
WebFetch("https://github.com/{org}/{repo}", "提取 Star 数、最近更新时间、维护状态和主要贡献者")
4. 技术方案对比
对比维度
对每个技术方案,从以下维度进行评估:
| 维度 | 评估内容 |
|---|---|
| 功能完整性 | 是否满足项目需求 |
| 性能 | 响应时间、吞吐量、资源消耗 |
| 生态系统 | 社区活跃度、插件丰富度、文档质量 |
| 学习曲线 | 团队学习成本、上手难度 |
| 成熟度 | 版本稳定性、生产案例、维护状态 |
| 扩展性 | 是否易于扩展和定制 |
| 兼容性 | 与其他技术的集成难度 |
| 成本 | 开发成本、运维成本、授权成本 |
对比表格模板
前端框架对比:
| 方案 | 优点 | 缺点 | 适用场景 | 推荐度 |
|---|---|---|---|---|
| Next.js | SSR/SSG、SEO友好、全栈能力 | 学习曲线陡、打包体积大 | 内容型网站、SEO要求高 | ⭐⭐⭐⭐⭐ |
| Vite + React | 开发体验好、构建快 | 需要自己配置路由等 | SPA、快速原型 | ⭐⭐⭐⭐ |
| Remix | 数据加载优雅、Web标准 | 生态较新、案例较少 | 数据密集型应用 | ⭐⭐⭐ |
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.
- 4d ago First seen · 270 lines · 27 tokens per session scan A cde2a8dccaed
architect/tech-research is a skill published in the GitHub repository echoVic/boss-skill (553 stars, last pushed 4d ago), licensed MIT. It adds 27 tokens to every session and 2,487 once invoked, about $0.0001 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.
Other skills, from other repositories
large-workspace-handling
To partition large workspaces (100+ files) into scoped subagent tasks when context is insufficient.
example-skill
Example skill template used for the CreateHub template. You should never use this skill directly as it is just a template made to be updated.
bmad-github-story-dev
Set up a git worktree/branch (or reuse the current one) and run BMAD dev-story end-to-end: auto-commits per task, PR creation, label updates. Use when the user invokes the SD menu code in bmad help, or asks to start implementing the next ready story, or asks to begin dev on a story.
bmad-github-story-sync
Reconcile GitHub state with BMAD files — detect merged PRs, mark stories done in sprint-status.yaml and story files, sync GitHub labels, and clean up worktrees and branches. Use when the user invokes the SS menu code in bmad help, or asks to sync BMAD with GitHub, or just merged a PR and wants BMAD updated.
bmad-github-story-create
Sync GitHub state then plan the next story end-to-end via the BMAD create-story flow. Detects blocking dependencies via GitHub labels and updates the GitHub issue label to ready. Use when the user invokes the SC menu code in bmad help, or asks to plan/create the next story, or asks to start the next BMAD story.
bmad-github-story-review
Run BMAD adversarial code review on the current story branch and push fixes. Does NOT mark the story done — the user merges the PR on GitHub. Use when the user invokes the SR menu code in bmad help, or asks to code-review the current story, or asks for an adversarial review of the open story PR.