Initial commit: coding harness feedback analysis

Harnesses under analysis:
- opencode (Go-based coding agent)
- pi (minimal terminal coding harness by Mario Zechner)
- hermes (Nous Research agent)
- forgecode (AI pair programmer with sub-agents)

Each harness folder contains:
- repo/: Source code from respective repositories
- feedback/localllm/: Community feedback for local/smaller models
- feedback/frontier/: Community feedback for frontier models

Research focus: Tool handling, skills systems, prompt engineering,
context management, and best practices for smaller/local models.

forgecode/feedback/localllm/qwen-3.5.md

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+# Qwen 3.5 with ForgeCode - Feedback Report
+
+**Model:** Qwen 3.5  
+**Provider:** Alibaba Cloud (via local inference)  
+**Harness:** ForgeCode  
+**Source References:** GitHub Issue #2894, Reddit r/LocalLLaMA  
+**Date Compiled:** April 9, 2026
+
+---
+
+## Known Issues
+
+### Multiple System Messages Bug
+**GitHub Issue:** #2894 (Open as of April 8, 2026)
+
+**Problem:** Multiple system messages break models with strict chat templates (e.g., Qwen3.5)
+
+**Error Manifestation:**
+- Models with strict chat templates fail to parse message structure correctly
+- Tool calling may fail or produce incorrect results
+- Agent behavior becomes unpredictable
+
+**Impact:**
+- Affects local inference with llama.cpp, Ollama, and similar servers
+- Qwen3.5 specifically mentioned as affected
+
+**Workaround Status:** No official fix yet; issue under investigation
+
+---
+
+## Tool Calling with Qwen Models
+
+### General Observations from Community
+
+1. **Qwen3-Coder Next** shows promise as "first usable coding model < 60GB"
+2. **Tool calling reliability varies** by inference backend:
+   - LM Studio 0.4.9 reportedly handles Qwen3.5 XML tool parsing more reliably than raw llama.cpp
+   - llama.cpp with `--jinja` flag helps with tool calling
+
+3. **finish_reason issue** is annoying to debug according to community reports
+
+---
+
+## Recommendations for Local Use
+
+1. **Use LM Studio** for more reliable tool parsing vs raw llama.cpp
+2. **Monitor system message count** - known issue with ForgeCode's multi-message approach
+3. **Test thoroughly** before relying on Qwen 3.5 for production tasks via ForgeCode
+
+---
+
+## Source References
+
+1. **GitHub Issue:** https://github.com/antinomyhq/forgecode/issues/2894
+2. **Reddit r/LocalLLaMA:** https://www.reddit.com/r/LocalLLaMA/comments/1sdhvc5/qwen_35_tool_calling_fixes_for_agentic_use_whats/