Analyze Research

Organization

devcodex-labs

analyze-research

技术调研子类型规范 — 技术选型/可行性评估/根因调查，只读工作流

Overview

Publisher	devcodex-labs
Repository	`devcodex`
Skill name	`analyze-research`
Stars	433
Forks	44
Bundled files	1
License	AGPL-3.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by devcodex-labs on GitHub. Read the source before you install it.

Installation

Install the Analyze Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/devcodex-labs/devcodex/tree/main/content/skills/analyze-research
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/devcodex-labs/devcodex.git /tmp/devcodex
mkdir -p .claude/skills
cp -r /tmp/devcodex/content/skills/analyze-research .claude/skills/analyze-research

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyze Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyze Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyze Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Analyze Research Skill

子类型标识：analyze.research

触发条件

用户要求调研、评估或比较某技术方案，主要目标是获得信息和建议（而非直接实施）。

场景	示例
技术选型	"对比 Redis/Memcached，推荐缓存方案"
可行性评估	"评估引入 GraphQL 的成本和收益"
概念验证	"验证 WebSocket 在我们架构下是否可行"
依赖调研	"调研 `@org/lib` 是否满足需求"
根因调查	"找出导致内存持续增长的根因"
隐性推荐/取舍	用户问"是否应该""哪个更好""有没有更好建议"，且结论会影响技术路线、产品/项目选择、时间/金钱投入或长期维护成本

⛔ 只读原则

调研过程中禁止修改任何项目源码文件。若结论需要代码变更，在报告中说明并建议切换到 dev/fix 工作流。

执行流程

步骤	动作
1	明确调研问题（一句话核心问题）
2	确认调研范围（深度 + 技术栈约束）
3	收集信息（profile + 源码 + 同类产品 / 项目 / 模块对比 + 依赖文档）并建立关联文件集合
4	分析评估（按调研类型，至少 3 轮）
5	收敛前再跑一次 CRS，确认关联文件集合无遗漏
6	PCV（收敛后汇总验证，含合理性 + 可实施性 + 收益）
7	输出明确结论（禁止模糊结论）
8	输出调研报告

统一联查矩阵（research 最小动作）

research 默认执行 analyze-lite 联查：关键词提取 → 关联文件集合 → 收敛前再跑一次 CRS
命中控制面、多真相源、模板-示例-校验链或单轮发现 ≥5 条 / 出现 🔴 问题时，应主动建议升级到 audit
ComparativeResearchGate 命中时，先比较同类产品 / 项目 / 本仓库相似模块 / 已有设计；若属于纯解释、低风险本地事实或用户明确要求快速答复，记录 N/A + skipReason，不得把普通问答默认升级成重调研
输入来自审查报告、AI review finding、audit issue 或代码评审发现时，必须执行 ReviewFindingIntakeGate：先把报告当线索补本地证据，再区分 must-fix、设计如此、用户决策、文档/实现漂移、测试覆盖缺口和未复现项

各类型输出格式

技术选型：

text
推荐：[方案名]
理由：[2~3句话，聚焦关键差异]
注意事项：[风险/限制]

可行性评估：

text
结论：[可行 / 有条件可行 / 不可行]
前置条件：[无则填"无"]
成本估算：[工程量/依赖变更/测试]
风险点：[主要风险]
备选方案：[若不可行]

依赖/兼容性评估：

text
业务源码平滑性：[当前源码/调用方/配置/公开契约是否需适配]
依赖层落地条件：[版本 / Node 或 peer dependency / lockfile / CI runner / 发布与文档要求]
纯依赖层零附加动作：[是 / 否 / N/A；给出证据]
内部共享库评估：[是否应修共享库 + 消费项目升级；若否说明理由]

根因调查：

text
现象：[观察到的问题]
根因链路：[现象 ← 直接原因 ← 根本原因]
影响范围：[受影响模块/接口/数据]
修复建议：[优先级排序的修复步骤]
预防措施：[避免复发的改进点]

输出

报告：reports/analysis/ 目录，遵循 report/SKILL.md 命名规则。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

intent.json1 KB

Frequently asked questions

What does the Analyze Research AI skill do?

技术调研子类型规范 — 技术选型/可行性评估/根因调查，只读工作流

Why use Analyze Research on TypingMind?

Because you install it once and use it with any model. Analyze Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyze Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/devcodex-labs/devcodex/tree/main/content/skills/analyze-research. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyze Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyze Research?

As many as you like. As long as a model supports skills, you can use Analyze Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyze Research AI skill free?

Yes. It is published on GitHub by devcodex-labs under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Analyze Research Skill

触发条件

⛔ 只读原则

执行流程

统一联查矩阵（research 最小动作）

各类型输出格式

输出

Bundled files

Frequently asked questions

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