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 agents/vericle/intellyweave/custom-agentsgit clone --depth 1 https://github.com/vericle/intellyweaveWrote 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/agents/vericle/intellyweave/custom-agents)<a href="https://agentmods.dev/agents/vericle/intellyweave/custom-agents"><img src="https://agentmods.dev/badge/agents/vericle/intellyweave/custom-agents.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01756 |
| Opus 5 | $0.00000 | $0.00878 |
| Sonnet 5 | $0.00000 | $0.00351 |
| Haiku 4.5 | $0.00000 | $0.00176 |
Grade A, and why
custom-agents 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Custom Agents
User-defined agents with dedicated knowledge bases that the Domain Router can automatically select.
What It Does
Custom Agents allow users to:
- Upload documents to create a dedicated knowledge base
- Define agent name, description, and system prompt
- Have IntellyWeave automatically route relevant queries to the agent
- Get responses grounded in the agent's knowledge base
Use When
- You have specialized documents for a specific domain
- You want automatic routing for domain-specific queries
- You need consistent, document-grounded responses
- You want to create expert assistants for specific topics
Creating Custom Agents
Via the UI
- Navigate to Agents & Remote Tools page
- Click Create Agent button
- Upload a document (PDF, TXT, DOCX, MD)
- Fill in agent details:
- Agent Name: Human-readable name (used for routing)
- Agent Description: What the agent specializes in (used for classification)
- System Prompt: Instructions defining agent behavior
Agent Configuration
| Field | Purpose | Example |
|---|---|---|
| Name | Identifies agent in router and UI | "Immigration Law Expert" |
| Description | Helps router classify queries | "Specializes in visa requirements and immigration procedures" |
| System Prompt | Defines agent behavior | "You are an expert in immigration law. Always cite specific sections..." |
| Document | Knowledge base source | Uploaded PDF or text file |
System Prompt Best Practices
You are a specialized expert in [domain]. Your knowledge is based on the
uploaded document. When answering questions:
- Focus on [specific topics]
- Cite specific sections from the document
- Explain complex concepts clearly
- Recommend professional consultation when needed
- Acknowledge when information is outside your knowledge base
UI Components
Agent Library
Location: frontend/app/components/agents/AgentLibrary.tsx
The main agent management interface:
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.
- 3d ago First seen · 293 lines · 0 tokens per session scan A 3f7e4f77bd31
custom-agents is an agent published in the GitHub repository vericle/intellyweave (75 stars, last pushed 7mo ago), licensed BSD-3-Clause. It costs nothing until one of its globs matches a file; then it loads 1,756 tokens. 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 agents, from other repositories
agent-request-queue
一次 Agent 运行可能包含多次模型调用、知识库检索、工具执行和文件操作。为了避免同一对话同时修改同一份上下文，Yuxi 把“收到请求”和“开始运行”分成两个阶段，并为每个线程维护 FIFO 队列。.
trellis-check
Code quality check expert. Reviews code changes against specs and self-fixes issues.
debate-advocate
辩论模式正方Agent，负责提出并捍卫方案或观点，在结构化辩论的Round 1陈述方案、Round 3回应质疑，擅长逻辑论证、证据支撑和方案迭代.
team-member
Standard AI Team OS team member agent.
opencode
Point OpenCode at a local rapid-mlx server. OpenCode is a Claude-Code-like terminal coding agent that speaks the OpenAI-compatible chat completions API (POST /v1/chat/completions) via the @ai-sdk/openai-compatible provider.
qwen-code
Point Qwen Code at a local rapid-mlx server. Qwen Code is Alibaba's gemini-cli fork tuned for Qwen tool-calling; it speaks the OpenAI-compatible chat completions API (POST /v1/chat/completions) via an OpenAI entry in modelProviders that maps 1:1 onto rapid-mlx's default endpoint.