Borrowing it
Nothing to install: this file belongs to xiaojilele-glitch/WhyBuddy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xiaojilele-glitch/WhyBuddy/main/.kiro/steering/competitive-landscape-2026-04-21.mdgit clone --depth 1 https://github.com/xiaojilele-glitch/WhyBuddyWrote 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/instructions/xiaojilele-glitch/whybuddy/competitive-landscape-2026-04-21)<a href="https://agentmods.dev/instructions/xiaojilele-glitch/whybuddy/competitive-landscape-2026-04-21"><img src="https://agentmods.dev/badge/instructions/xiaojilele-glitch/whybuddy/competitive-landscape-2026-04-21/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/instructions/xiaojilele-glitch/whybuddy/competitive-landscape-2026-04-21"><img src="https://agentmods.dev/badge/instructions/xiaojilele-glitch/whybuddy/competitive-landscape-2026-04-21.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00600 | $0.00600 |
| Opus 5.5 | $0.00240 | $0.00240 |
| Sonnet 5.5 | $0.00120 | $0.00120 |
| Haiku 4.5 | $0.00060 | $0.00060 |
Grade A, and why
WhyBuddy competitive-landscape-2026-04-21.md 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 1mo 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
竞争格局快照（2026-04-21）
文档目的
这份说明文档用于澄清平台定位。目标不是声称 GitHub 上完全没有类似开源平台，而是明确 SlideRule 真正还能形成差异化的位置。
市场现实
目前 GitHub 上已经存在不少覆盖相邻问题空间的开源项目，例如：
- Dify：应用构建、工作流编排、知识库、Agent 能力
- Flowise：可视化 LLM 工作流与 Agent 构建器
- Langflow：面向 LLM 系统的可视化流程编辑
- n8n：通用自动化平台，正在持续增强 AI 工作流能力
- LangGraph 生态：图式 / 状态化 Agent 编排
- AutoGen 生态：多 Agent 协作与编排
- RAGFlow：偏 RAG 和知识处理的平台
- Mastra / CrewAI 一类生态：强调 Agent 与工作流运行时抽象
Cube 仍然可以形成的差异化
SlideRule 可以占据一个更少见的组合位置：
- 图式编排能力 + mission-native 执行模型
- 内建 replay、audit、lineage 与 operator control
- 更偏 office / task operating model，而不是单纯开发者画布
- 多模态、RAG、权限治理、外部执行器链路一体化
- 可以把 graph instance 投影进已经存在的 mission / task runtime
战略结论
更准确、更稳妥的说法应该是：
“相邻平台已经存在，但真正同时把图式 Agent 编排、mission 运行时、回放、审计、operator control、office-native 执行壳整合到一套系统中的平台并不多。”
这个判断，比“GitHub 上完全没有这种平台”更准确，也更有说服力。
对文档体系的启发
超细文档仍然是优势，但前提是：
- 能体现集成深度
- 能维护整体架构一致性
- 能真正指导迁移执行
- 不是简单堆一批互不相关的 Markdown
这也是为什么 50+ 文档体系必须采用分层结构，而不能平铺。
对外表达建议
以后在路线图或对外描述里，建议：
- 避免绝对化的“全球首创 / GitHub 无同类”表述
- 强调平台集成深度，而不是只强调节点数量
- 强调 replay、governance、operator-facing runtime 这些组合能力
- 把
web-aigc迁移表述为“能力增强”，而不是“整个平台克隆”
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.
- 1mo ago First seen · 61 lines · 600 tokens per session scan A 7ee35787b8c7
WhyBuddy competitive-landscape-2026-04-21.md is an instructions file published in the GitHub repository xiaojilele-glitch/WhyBuddy (380 stars, last pushed 1mo ago), licensed MIT. It adds 600 tokens to every session, about $0.0024 per session on Opus 5.5. 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 2026-09-23.
WhyBuddy competitive-landscape-2026-04-21.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| WhyBuddy competitive-landscape-2026-04-21.mdxiaojilele-glitch/WhyBuddy | Instructions file | 380 | 1mo ago | MIT | A | 600 | Kiro |
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