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 skills/felipeslo/opencode-kit/intelligent-routingnpx skills add felipeslo/opencode-kit --skill intelligent-routinggit clone --depth 1 https://github.com/felipeslo/opencode-kitWhat 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 | $0.00032 | $0.02466 |
| Opus 5 | $0.00016 | $0.01233 |
| Sonnet 5 | $0.00006 | $0.00493 |
| Haiku 4.5 | $0.00003 | $0.00247 |
Grade A, and why
intelligent-routing 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
91% identical to intelligent-routing — 13 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 — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intelligent Agent Routing
Purpose: Automatically analyze user requests and route them to the most appropriate specialist agent(s) without requiring explicit user mentions.
Core Principle
The AI should act as an intelligent Project Manager, analyzing each request and automatically selecting the best specialist(s) for the job.
How It Works
1. Request Analysis
Before responding to ANY user request, perform automatic analysis:
graph TD
A[User Request: Add login] --> B[ANALYZE]
B --> C[Keywords]
B --> D[Domains]
B --> E[Complexity]
C --> F[SELECT AGENT]
D --> F
E --> F
F --> G[security-auditor + backend-specialist]
G --> H[AUTO-INVOKE with context]
2. Agent Selection Matrix
Use this matrix to automatically select agents:
| User Intent | Keywords | Selected Agent(s) | Auto-invoke? |
|---|---|---|---|
| Authentication | "login", "auth", "signup", "password" | security-auditor + backend-specialist |
✅ YES |
| UI Component | "button", "card", "layout", "style" | frontend-specialist |
✅ YES |
| Mobile UI | "screen", "navigation", "touch", "gesture" | mobile-developer |
✅ YES |
| API Endpoint | "endpoint", "route", "API", "POST", "GET" | backend-specialist |
✅ YES |
| Database | "schema", "migration", "query", "table" | database-architect + backend-specialist |
✅ YES |
| Bug Fix | "error", "bug", "not working", "broken" | debugger |
✅ YES |
| Test | "test", "coverage", "unit", "e2e" | test-engineer |
✅ YES |
| Deployment | "deploy", "production", "CI/CD", "docker" | devops-engineer |
✅ YES |
| Security Review | "security", "vulnerability", "exploit" | security-auditor + penetration-tester |
✅ YES |
| Performance | "slow", "optimize", "performance", "speed" | performance-optimizer |
✅ YES |
| Product Def | "requirements", "user story", "backlog", "MVP" | product-owner |
✅ YES |
| New Feature | "build", "create", "implement", "new app" | orchestrator → multi-agent |
⚠️ ASK FIRST |
| Complex Task | Multiple domains detected | orchestrator → multi-agent |
⚠️ ASK FIRST |
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 · 335 lines · 32 tokens per session scan A 50d6da26d714
intelligent-routing is a skill published in the GitHub repository felipeslo/opencode-kit (2 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 2,466 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to intelligent-routing, differing in 13 lines, and is treated as a copy.
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