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/code-reviewWrote 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/code-review)<a href="https://agentmods.dev/skills/tencentcloud/octop/code-review"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/code-review/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/code-review"><img src="https://agentmods.dev/badge/skills/tencentcloud/octop/code-review.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 | $0.00058 | $0.00827 |
| Opus 5.5 | $0.00023 | $0.00331 |
| Sonnet 5.5 | $0.00012 | $0.00165 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
code-review 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 code-review — 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/code-review
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Review code changes with a structured lens on security, performance, correctness, and maintainability.
Usage
/code-review <PR URL or file path>
Review the provided code changes: @$1
If no specific file or URL is provided, ask what to review.
How It Works
┌─────────────────────────────────────────────────────────────────┐
│ CODE REVIEW │
├─────────────────────────────────────────────────────────────────┤
│ STANDALONE (always works) │
│ ✓ Paste a diff, PR URL, or point to files │
│ ✓ Security audit (OWASP top 10, injection, auth) │
│ ✓ Performance review (N+1, memory leaks, complexity) │
│ ✓ Correctness (edge cases, error handling, race conditions) │
│ ✓ Style (naming, structure, readability) │
│ ✓ Actionable suggestions with code examples │
├─────────────────────────────────────────────────────────────────┤
│ SUPERCHARGED (when you connect your tools) │
│ + Source control: Pull PR diff automatically │
│ + Project tracker: Link findings to tickets │
│ + Knowledge base: Check against team coding standards │
└─────────────────────────────────────────────────────────────────┘
Review Dimensions
Security
- SQL injection, XSS, CSRF
- Authentication and authorization flaws
- Secrets or credentials in code
- Insecure deserialization
- Path traversal
- SSRF
Performance
- N+1 queries
- Unnecessary memory allocations
- Algorithmic complexity (O(n²) in hot paths)
- Missing database indexes
- Unbounded queries or loops
- Resource leaks
Correctness
- Edge cases (empty input, null, overflow)
- Race conditions and concurrency issues
- Error handling and propagation
- Off-by-one errors
- Type safety
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 · 119 lines · 58 tokens per session scan A 6303932f1b30
code-review is a skill published in the GitHub repository TencentCloud/Octop (9,540 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 827 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 code-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
sage-review
Deep, platform-neutral code review for PRs and CRs in ONE thorough single pass — design reasoning (Problem Worth Solving & Solution Fit) as one dimension alongside the 9 code-level dimensions, with chain-of-consequences, self-critique, and draft-only comments. The single app-owned source of truth.
learn-from-sage
Detection-gap (miss) analysis for Code Review Sage. Learn from shipped fixes, acted-on human comments, and design outcomes to close reviewer blind spots. Inline during review stages a candidate; a human triggers a one-shot AI consolidation into the live ruleset.
review-fix-signoff-loop
Use when writing Agent Relay or Ricky workflows that must loop review, fix, and validation with fresh agent context until independent signoff agents, typically Claude and Codex, both agree the work is comprehensively complete. Covers fresh-context iterations, repairable gates, dual reviewer verdict contracts…
simplify
Clean up changed code while preserving intended behavior. Use when the user asks to simplify or improve code quality through reuse, simplification, efficiency, and abstraction reviews. Correctness bug hunting is outside scope.
control-center-review
Review one captured Control Center build before runtime activation.
review-pr
Review GitHub pull requests. Use when user says "review PR", "review pull request", or "/review-pr".