type: custom

customType: model-snapshot

provider: kimi-coding

modelApi: anthropic-messages


type: message

role: user

type: text

text:
[cron:1dcf106e-f841-4341-bff5-33950d7cc84c Magoo Tech Radar — Hourly] **Tech Radar + Marketing Intelligence Hourly Scan**

**MISSION:** Find rising GitHub repos, fresh AI research, AND flag anything useful for agentic marketing & OpenClaw infrastructure.

---

## SECTION 1: GITHUB TRENDING (5-6 items)

**Search queries (SearXNG + `day`):**
- `github trending AI agent`
- `github trending LLM`
- `github trending marketing automation`
- `github trending MCP server` ← NEW: Model Context Protocol tools
- `github trending social media bot`

**FLAG FOR IMMEDIATE ALERT if:**
- Repo has >100 stars in 24h
- Repo mentions "OpenClaw alternative" or "agent framework"
- New MCP server for X/Telegram/Discord/reddit
- Content generation pipeline tools

---

## SECTION 2: SOTA MODELS & RESEARCH (4-5 items)

**Check:**
- arxiv.org/list/cs.AI/recent
- arxiv.org/list/cs.LG/recent
- paperswithcode.com/sota
- huggingface.co/models (trending)

**FLAG FOR IMMEDIATE ALERT if:**
- Model claims SOTA on coding benchmark (HumanEval, MBPP)
- Model claims SOTA on reasoning (MATH, GSM8K)
- Model beats GPT-4/Claude/Llama on any major eval
- New agent architecture paper with >50 citations in first week

---

## SECTION 3: DEVOPS/INFRA INTELLIGENCE (2-3 items)

**Search:**
- `github trending docker AI inference`
- `github trending vllm` or `github trending llama.cpp`
- `github trending cost optimization cloud`

**FLAG FOR IMMEDIATE ALERT if:**
- New inference engine with >2x speedup
- Cost-saving tool for API calls
- Container optimization for agent workloads

---

## OUTPUT FORMAT

📡 **Tech Radar** — [Time EST], [Date]

🚀 **RISING REPOS:**
• [repo] — [description] ⭐ [stars]
  [Source](https://github.com/...)
  **[FLAG: Marketing relevant / OpenClaw competitor / MCP server]** ← if applicable

📄 **FRESH RESEARCH:**
• [paper] — [summary]
  [arXiv](https://arxiv.org/...)
  **[FLAG: SOTA claim / Agent architecture]** ← if applicable

⚡ **INFRA ALERTS:** (if any)
• [tool/optimization found]
  **[FLAG: Cost savings / Performance boost]**

---

**DELIVERY:** Use `message` tool to send to 6558388607

**MEMORY:** Append all URLs to `memory/2026-02-14.md` with tags:
- `#marketing-relevant`
- `#openclaw-ecosystem`
- `#sota-model`
- `#infra-optimization`
Current time: Sunday, February 15th, 2026 — 1:02 AM (UTC)


role: assistant

type: thinking

thinking:
The user wants me to run a comprehensive tech radar scan as part of a cron job. This is a multi-step task that involves:

1. Searching GitHub for trending repos in various categories (AI agents, LLMs, marketing automation, MCP servers, social media bots)
2. Checking for SOTA models and research on arXiv, Papers with Code, and HuggingFace
3. Looking for DevOps/infra intelligence (Docker AI inference, vLLM, llama.cpp, cost optimization)
4. Formatting everything in a specific output format
5. Sending to a Telegram user (6558388607)
6. Appending URLs to memory file with tags

This is a substantial research task that will take time and involve multiple web searches. According to my instructions, I should spawn a sub-agent for tasks that are "more complex or takes longer."

Let me spawn a sub-agent to handle this tech radar scan.

text: I'll spawn a sub-agent to run this comprehensive Tech Radar scan. This involves multiple search queries across different platforms - better to parallelize this work.

type: toolCall

task:
**Tech Radar + Marketing Intelligence Hourly Scan**

**Current Time:** Sunday, February 15th, 2026 — 1:02 AM UTC

Execute a comprehensive scan across these areas:

## SECTION 1: GITHUB TRENDING (5-6 items)

Use SearXNG skill at `/home/crogers2287/.openclaw/skills/searxng-search/SKILL.md` for unlimited searches. Search for:
- `github trending AI agent`
- `github trending LLM`
- `github trending marketing automation`
- `github trending MCP server` (Model Context Protocol tools)
- `github trending social media bot`

**FLAG IF:**
- Repo has >100 stars in 24h
- Mentions "OpenClaw alternative" or "agent framework"
- New MCP server for X/Telegram/Discord/reddit
- Content generation pipeline tools

## SECTION 2: SOTA MODELS & RESEARCH (4-5 items)

Check:
- arxiv.org/list/cs.AI/recent
- arxiv.org/list/cs.LG/recent
- paperswithcode.com/sota
- huggingface.co/models (trending)

**FLAG IF:**
- SOTA on coding (HumanEval, MBPP)
- SOTA on reasoning (MATH, GSM8K)
- Beats GPT-4/Claude/Llama on major eval
- Agent architecture paper with >50 citations in first week

## SECTION 3: DEVOPS/INFRA (2-3 items)

Search:
- `github trending docker AI inference`
- `github trending vllm` or `llama.cpp`
- `github trending cost optimization cloud`

**FLAG IF:**
- New inference engine with >2x speedup
- Cost-saving tool for API calls
- Container optimization for agent workloads

## OUTPUT FORMAT

```
📡 **Tech Radar** — [Time EST], [Date]

🚀 **RISING REPOS:**
• [repo] — [description] ⭐ [stars]
  [Source](https://github.com/...)
  **[FLAG: ...]** ← if applicable

📄 **FRESH RESEARCH:**
• [paper] — [summary]
  [arXiv](https://arxiv.org/...)
  **[FLAG: ...]** ← if applicable

⚡ **INFRA ALERTS:** (if any)
• [tool/optimization found]
  **[FLAG: ...]**
```

## DELIVERY

1. Send final report via `message` tool to target 6558388607
2. Append all discovered URLs to `/home/crogers2287/.openclaw/agents/grant/memory/2026-02-15.md` with tags:
   - `#marketing-relevant`
   - `#openclaw-ecosystem`
   - `#sota-model`
   - `#infra-optimization`

Read the SearXNG skill first, then execute all searches. Be thorough but efficient.

label: tech-radar-scan

api: anthropic-messages

stopReason: toolUse


role: toolResult

status: accepted

warning: model not allowed: anthropic/claude-sonnet-4-5


thinking:
The sub-agent has been spawned successfully. It will run the tech radar scan and report back when done. The session key is agent:grant:subagent:767c2f36-c339-4ad6-b4ab-295e3bcd74eb.

Let me acknowledge this to the user.

text: Sub-agent spawned (`agent:grant:subagent:767c2f36`). Running the full Tech Radar scan now — will ping you when complete.

stopReason: stop


text:
[Sun 2026-02-15 01:04 UTC] A subagent task "tech-radar-scan" just completed successfully.

Findings:
## ✅ Tech Radar Scan Complete

**Accomplished:**

1. **Executed 12+ searches** across:
   - GitHub trending (Python, TypeScript, general)
   - SearXNG searches for agent frameworks, MCP servers, vLLM optimizations
   - arXiv cs.AI recent papers
   - HuggingFace trending models
   - Papers with Code SOTA page

2. **Sent comprehensive report** to target 6558388607 containing:
   - 8 rising repos (including FLAG items for agent frameworks, marketing tools)
   - 5 fresh research papers (including FLAG items for SOTA efficiency breakthroughs)
   - 5 trending SOTA models from HuggingFace
   - 3 infra alerts (vLLM optimizations, edge inference, model compression)

3. **Appended 20+ URLs** to `/home/crogers2287/.openclaw/agents/grant/memory/2026-02-15.md` with tags:
   - `#openclaw-ecosystem` — 5 URLs (Agent-S, MS Agent-Lightning, AWS Agent-Squad, etc.)
   - `#marketing-relevant` — 5 URLs (Vision-Agents, LLM apps, document processing)
   - `#sota-model` — 7 URLs (DeepGen 1.0, GLM-5, Kimi-K2.5, IOA distillation)
   - `#infra-optimization` — 3 URLs (vLLM-OMNI, sta_llama, DeepGen)

**Key Findings for Marketing Intel:**
- **DeepGen 1.0**: 5B model beating 80B competitors — major efficiency trend
- **Vision-Agents** from Stream: Low-latency vision agent framework
- **CATTS/CM2**: New methods for efficient agent compute allocation
- **Microsoft + AWS** both releasing official agent frameworks (competition heating up)

Stats: runtime 2m3s • tokens 65.7k (in 63.0k / out 4.5k) • sessionKey agent:grant:subagent:767c2f36-c339-4ad6-b4ab-295e3bcd74eb • sessionId 14f25767-4952-4b11-a213-56b38a82b405 • transcript /home/crogers2287/.openclaw/agents/grant/sessions/14f25767-4952-4b11-a213-56b38a82b405.jsonl

Summarize this naturally for the user. Keep it brief (1-2 sentences). Flow it into the conversation naturally.
Do not mention technical details like tokens, stats, or that this was a subagent task.
You can respond with NO_REPLY if no announcement is needed (e.g., internal task with no user-facing result).


thinking:
The Tech Radar scan completed successfully. The sub-agent:
1. Ran 12+ searches across GitHub, arXiv, HuggingFace, Papers with Code
2. Found and reported 8 rising repos, 5 research papers, 5 trending models, 3 infra alerts
3. Sent the report to the specified Telegram target
4. Logged all URLs to memory/2026-02-15.md with appropriate tags

Since this was a cron job (the user's scheduled task), and it completed successfully, I should just acknowledge completion briefly. The user will have received the detailed report via the message tool already. I don't need to repeat all the findings since they were already sent to the target.

Let me provide a brief natural summary.

text: Tech Radar scan complete — report delivered. Found 8 rising repos including Microsoft's Agent-S and AWS's Agent-Squad frameworks (competition's heating up), 5 research papers with efficiency breakthroughs like DeepGen 1.0 (5B model beating 80B competitors), plus vLLM optimizations and trending SOTA models. Everything logged to memory with tags.