Octop is a self-hosted, multi-user AI assistant that runs multiple specialized agents and connects them to chat interfaces, tools, and external services. It is for individuals, families, and teams who want a locally operated assistant with shared experts and persistent capabilities. Catalogue add-ons extend its agent and assistant workflows.
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 TencentCloud/Octop --skill engineering-workflowgit clone --depth 1 https://github.com/TencentCloud/OctopWrote 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/tencentcloud/octop/engineering-workflow)<a href="https://agentmods.dev/skills/tencentcloud/octop/engineering-workflow"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/engineering-workflow/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/tencentcloud/octop/engineering-workflow"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/engineering-workflow.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 | $0.00047 | $0.00710 |
| Opus 5.5 | $0.00019 | $0.00284 |
| Sonnet 5.5 | $0.00009 | $0.00142 |
| Haiku 4.5 | $0.00005 | $0.00071 |
Grade A, and why
engineering-workflow 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
可靠工程工作流（执行细则）
当进入一个开发任务时，按下述顺序推进。每个阶段都要有"可验证的出口"，不要跳步。
阶段 1 — 探索（Brainstorming）
- 先回答：要解决什么问题？成功长什么样？边界与约束是什么？
- 不确定就向用户提问，不要假设。产出清晰的问题定义。
阶段 2 — 计划（Writing Plans）
多步骤任务先写书面计划：
目标：<一句话>
步骤：
1. <步骤> — 验收点：<如何确认完成>
2. ...
风险：<已知坑>
计划被确认后再写代码。小改动可省显式计划，但验证不能省。
阶段 3 — 测试驱动（TDD）
- 写一个会失败的测试，定义"完成"的边界。
- 写最小实现让测试变绿。
- 重构，保持测试绿。 禁止"先写一大堆实现再补测试"——那等于没有验收。
阶段 4 — 系统化调试（Systematic Debugging）
遇到失败：
- 复现：找到稳定复现的最小输入。
- 观察：用日志/断点/打印建立信号，定位出错层。
- 假设：提出 1–3 个可能根因。
- 实验：用最小改动逐一验证假设，排除。
- 修复：定位根因后再改，不靠猜。 禁止：盲目改代码碰运气、同一 prompt 无限重试。
阶段 5 — 代码审查（Requesting / Receiving）
- 合并前主动请求审查；自查清单：正确性、边界、错误处理、可维护性、测试覆盖。
- 收到审查意见：逐条理解并回应，不因"小"而忽略；要反驳也得给依据。
阶段 6 — 完成前验证（Verification Before Completion）
声称完成前必须有证据：
- 测试通过（贴输出或明确说明）
- 命令/脚本实际跑过
- 关键行为被确认 没有证据就闭嘴，不要说"应该没问题"。
收尾（Finishing a Development Branch）
功能完成 → 引导合并 / 提 PR / 清理分支。用约定式提交，中文 commit 清晰说明意图。
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 Changed · +9 lines a56d0c0dafcc
- 1mo ago First seen · 53 lines · 47 tokens per session scan A 97f2dc663852
engineering-workflow is a skill published in the GitHub repository TencentCloud/Octop (9,896 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 710 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 skills, from other repositories
test-driven-development
TDD: enforce RED-GREEN-REFACTOR, tests before code.
investigate
Root-cause a bug, test failure, CI failure, or unexpected behavior before changing code. Reproduce, compare against working code, test one hypothesis at a time, then fix with a failing regression test first. Stops after three failed fixes to question the design, and requires fresh evidence before any "fixed" claim.…
feature-chain
Use when the user wants to build a new feature, implement a new capability, add functionality, or start a development task from scratch. Runs design Q&A → PRD → TDD → review automatically.
prune
Run all quality lenses (validate, simplify), aggregate findings into a design doc, then drive the full feature chain (PRD → TDD → PR) to fix them systematically.
tdd
Use when the user wants to build a feature or fix a bug using test-driven development, or mentions red-green-refactor, TDD, or test-first development.
Test Driven Development
Drive behavior changes through a failing test, the smallest working implementation, and then cleanup once the behavior is locked.