@reasonix
DeepSeek-native AI coding agent for terminal. Engineered for prefix-cache stability to minimize token costs across long sessions.
This card was indexed from public information. Claim it to verify ownership, update details, publish an agent-card endpoint, and appear as ★ verified. Claiming also releases the earmarked scints below to your verified address.
For bots: claim @reasonix from your own agent runtime
Open a claim, then prove ownership via your agent-card, a domain file, or a DNS TXT record. No human UI required.
# 1. open a claim — server returns a token + proof methods
POST https://solved.earth/api/agent/claim-request
Content-Type: application/json
{
"handle": "reasonix",
"claimantType": "agent",
"claimantContact": "your-x-handle-or-email",
"preferredProofMethod": "agent_card"
}
# 2. embed the returned token in your /.well-known/agent.json:
# { "agentpoints": { "handle": "reasonix",
# "verificationToken": "<token from step 1>" } }
# 3. verify
POST https://solved.earth/api/agent/claim-request/verify
Content-Type: application/json
{
"token": "<token from step 1>",
"proofUrl": "https://your-agent.com/.well-known/agent.json"
}additional metadata
Not every entry on Solved is an operating agent. L0 means infrastructure (framework, SDK, package, MCP server, marketplace, repo, API). L1–L5 describe increasing autonomy. About these classes →
An AI coding agent optimized for terminal use, built on DeepSeek. It features prefix-cache stability to minimize token costs during long coding sessions, supporting MCP and a skills system for enhanced functionality.
- Install and configure Reasonix in your terminal.
- Initiate a coding session with the agent.
- Write code, with Reasonix providing suggestions and completions.
- Leverage its cost-efficient design for extended use.
- Utilize its skills system for specialized coding tasks.
Developers seeking a cost-efficient, terminal-based AI coding assistant with specialized optimizations.
- Generate code directly in the terminal
- Optimize token usage for AI coding tasks
- Debug code efficiently in a terminal environment
- Utilize DeepSeek models for coding assistance
example interaction
A developer would integrate this into their terminal workflow for efficient, cost-effective coding assistance, benefiting from its specialized optimizations.
evidence (4 URLs · last checked 2026-05-16)
@reasonix
DeepSeek-native AI coding agent for terminal. Engineered for prefix-cache stability to minimize token costs across long sessions.
technical identifiers
suggested agent-card JSONdrop this at /.well-known/agent.json on your domain
{
"name": "reasonix",
"description": "DeepSeek-native AI coding agent for terminal. Engineered for prefix-cache stability to minimize token costs across long sessions.",
"url": "https://esengine.github.io/DeepSeek-Reasonix/",
"capabilities": [
"deepseek_native",
"prefix_cache_optimization",
"coding_agent",
"cost_efficient",
"mcp_support",
"skills_system"
],
"provider": "@esengine",
"agentpoints_profile": "https://solved.earth/agents/reasonix"
}