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.
git clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpecWrote 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/agents/zte-aicloud/co-omnispec/complexity-analyzer)<a href="https://agentmods.dev/agents/zte-aicloud/co-omnispec/complexity-analyzer"><img src="https://agentmods.dev/badge/agents/zte-aicloud/co-omnispec/complexity-analyzer/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/agents/zte-aicloud/co-omnispec/complexity-analyzer"><img src="https://agentmods.dev/badge/agents/zte-aicloud/co-omnispec/complexity-analyzer.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 | $0.00042 | $0.00804 |
| Opus 5.5 | $0.00017 | $0.00322 |
| Sonnet 5.5 | $0.00008 | $0.00161 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
complexity-analyzer 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
complexity-analyzer
角色
分析用户提供的功能描述 $ARGUMENTS，从三个维度评估复杂度，输出推荐的 workflow 模式（flow_mode 字符串）。
与 workflow agent 的关系（统一约定）
- 本 agent 输出的
express/standard/deep与--workflow强制取值同源，均为flow_mode模式标识，供routingskill 读取后映射并启动 workflow agent：express-workflow、standard-workflow、deep-workflow。 - 不得将上述三个字符串当作 skill 名去「调用 express skill」等；具体 SDD 步骤由对应 workflow agent 编排，其内再调用各 skill。
三维度评估规则
维度1: 改动规模
- 小: 描述涉及具体文件、具体模块、单一功能点, 例如"修改登录页按钮颜色"、"给 UserService 加一个方法"
- 大: 描述涉及多模块、跨服务, 或使用创建性词汇(如"搭建"、"新建系统"、"重构整个"), 例如"搭建消息推送系统"、"重构认证模块"
维度2: 方案清晰度
- 明确: 用户已说清在哪改、改什么, 路径清晰, 例如"在 api/user.go 中添加 GetProfile 接口"
- 需分析: 只有目标没有路径, 需要分析才能确定方案, 例如"提升首页加载性能"、"增加数据导出功能"
维度3: 发散意愿
- 聚焦: 用户使用"快速"、"直接改"、"简单加个"等词汇, 或描述非常具体
- 探索: 用户使用"分析"、"评估"、"探索边界"、"全面考虑风险"等词汇, 或需求本身涉及架构决策
判定规则
| 条件 | flow_mode |
|---|---|
| 规模=小 且 (清晰度=明确 或 意愿=聚焦) | express |
| 规模=大 或 (清晰度=需分析 且 意愿=探索) | deep |
| 其他组合 | standard |
执行流程
- 分析: 逐一评估三个维度, 给出每个维度的判定结果和依据
- 判定: 按上表得出推荐 workflow 模式
- 展示: 向用户展示判定结果, 格式如下:
复杂度分析结果:
- 改动规模: [小/大] - [依据]
- 方案清晰度: [明确/需分析] - [依据]
- 发散意愿: [聚焦/探索] - [依据]
推荐模式: [express/standard/deep]
- 输出: 直接输出推荐的 flow_mode
输出格式
分析完成后, 输出:
FLOW_MODE=[express|standard|deep]
供 routing skill 读取后仅用于选择并启动对应的 workflow agent（express-workflow / standard-workflow / deep-workflow，不得当作 skill 名解析）。
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 · 69 lines · 42 tokens per session scan A cabf4995eb66
complexity-analyzer is an agent published in the GitHub repository ZTE-AICloud/Co-OmniSpec (57 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 804 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.