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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/TencentCloud/Octopnpx agentmods add skills/tencentcloud/octop/architectureWrote 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/architecture)<a href="https://agentmods.dev/skills/tencentcloud/octop/architecture"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/architecture/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/architecture"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/architecture.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 | $0.00052 | $0.00553 |
| Opus 5.5 | $0.00021 | $0.00221 |
| Sonnet 5.5 | $0.00010 | $0.00111 |
| Haiku 4.5 | $0.00005 | $0.00055 |
Grade A, and why
architecture 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 today.
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.
This is a copy
100% identical to architecture — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/architecture
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Create an Architecture Decision Record (ADR) or evaluate a system design.
Usage
/architecture $ARGUMENTS
Modes
Create an ADR: "Should we use Kafka or SQS for our event bus?" Evaluate a design: "Review this microservices proposal" System design: "Design the notification system for our app"
See the system-design skill for detailed frameworks on requirements gathering, scalability analysis, and trade-off evaluation.
Output — ADR Format
# ADR-[number]: [Title]
**Status:** Proposed | Accepted | Deprecated | Superseded
**Date:** [Date]
**Deciders:** [Who needs to sign off]
## Context
[What is the situation? What forces are at play?]
## Decision
[What is the change we're proposing?]
## Options Considered
### Option A: [Name]
| Dimension | Assessment |
|-----------|------------|
| Complexity | [Low/Med/High] |
| Cost | [Assessment] |
| Scalability | [Assessment] |
| Team familiarity | [Assessment] |
**Pros:** [List]
**Cons:** [List]
### Option B: [Name]
[Same format]
## Trade-off Analysis
[Key trade-offs between options with clear reasoning]
## Consequences
- [What becomes easier]
- [What becomes harder]
- [What we'll need to revisit]
## Action Items
1. [ ] [Implementation step]
2. [ ] [Follow-up]
If Connectors Available
If ~~knowledge base is connected:
- Search for prior ADRs and design docs
- Find relevant technical context
If ~~project tracker is connected:
- Link to related epics and tickets
- Create implementation tasks
Tips
- State constraints upfront — "We need to ship in 2 weeks" or "Must handle 10K rps" shapes the answer.
- Name your options — Even if you're leaning one way, I'll give a more balanced analysis with explicit alternatives.
- Include non-functional requirements — Latency, cost, team expertise, and maintenance burden matter as much as features.
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.
- today First seen · 86 lines · 52 tokens per session scan A de7db3170a3a
architecture is a skill published in the GitHub repository TencentCloud/Octop (9,540 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 553 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to architecture, differing in 0 lines, and is treated as a copy.
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