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 agentmods add commands/shyftlabs/continuum/code-review-swarmgit clone --depth 1 https://github.com/shyftlabs/continuumWhat 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 | $0.00000 | $0.02883 |
| Opus 5 | $0.00000 | $0.01442 |
| Sonnet 5 | $0.00000 | $0.00577 |
| Haiku 4.5 | $0.00000 | $0.00288 |
Grade A, and why
code-review-swarm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to code-review-swarm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 514 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Swarm - Automated Code Review with AI Agents
Overview
Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis.
Core Features
1. Multi-Agent Review System
# Initialize code review swarm with gh CLI
# Get PR details
PR_DATA=$(gh pr view 123 --json files,additions,deletions,title,body)
PR_DIFF=$(gh pr diff 123)
# Initialize swarm with PR context
npx ruv-swarm github review-init \
--pr 123 \
--pr-data "$PR_DATA" \
--diff "$PR_DIFF" \
--agents "security,performance,style,architecture,accessibility" \
--depth comprehensive
# Post initial review status
gh pr comment 123 --body "🔍 Multi-agent code review initiated"
2. Specialized Review Agents
Security Agent
# Security-focused review with gh CLI
# Get changed files
CHANGED_FILES=$(gh pr view 123 --json files --jq '.files[].path')
# Run security review
SECURITY_RESULTS=$(npx ruv-swarm github review-security \
--pr 123 \
--files "$CHANGED_FILES" \
--check "owasp,cve,secrets,permissions" \
--suggest-fixes)
# Post security findings
if echo "$SECURITY_RESULTS" | grep -q "critical"; then
# Request changes for critical issues
gh pr review 123 --request-changes --body "$SECURITY_RESULTS"
# Add security label
gh pr edit 123 --add-label "security-review-required"
else
# Post as comment for non-critical issues
gh pr comment 123 --body "$SECURITY_RESULTS"
fi
Performance Agent
# Performance analysis
npx ruv-swarm github review-performance \
--pr 123 \
--profile "cpu,memory,io" \
--benchmark-against main \
--suggest-optimizations
Architecture Agent
# Architecture review
npx ruv-swarm github review-architecture \
--pr 123 \
--check "patterns,coupling,cohesion,solid" \
--visualize-impact \
--suggest-refactoring
3. Review Configuration
# .github/review-swarm.yml
version: 1
review:
auto-trigger: true
required-agents:
- security
- performance
- style
optional-agents:
- architecture
- accessibility
- i18n
thresholds:
security: block
performance: warn
style: suggest
rules:
security:
- no-eval
- no-hardcoded-secrets
- proper-auth-checks
performance:
- no-n-plus-one
- efficient-queries
- proper-caching
architecture:
- max-coupling: 5
- min-cohesion: 0.7
- follow-patterns
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.
- yesterday First seen · 514 lines · 0 tokens per session scan A 9e00b9eb6de5
code-review-swarm is a command published in the GitHub repository shyftlabs/continuum (83 stars, last pushed 10d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,883 tokens. A static security scan graded it A with 0 findings. It is 100% identical to code-review-swarm, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
agentlas-graph
Build an Agentlas automation by describing it, list saved ones, or request a run.
agentlas-orch
Set or show which model runs the orchestrator and which runs the workers.
agentlas-storm
Run a force-robust Stormbreaker loop — route to real agents, execute a verified pipeline to completion.
agentlas-login
Sign this machine into Agentlas (opens the browser sign-in window).
auto-canary
배포 검증 — build, E2E, 브라우저 건강 검진을 실행합니다.
auto-setup
프로젝트 컨텍스트 생성 — 코드베이스를 분석하고 ARCHITECTURE.md 및 .autopus/project 문서를 생성합니다.