Unify feedback file structure across harness folders

Applied unified structure template to key feedback files:

Structure now includes:
1. Standard header (Model/Size/Provider/Harness/Date)
2. Quick Reference table
3. Benchmark Results (with harness+model note)
4. What Worked Well
5. Issues Encountered (with severity levels)
6. Configuration (if applicable)
7. Source References (with descriptions)

Files restructured:
- forgecode/feedback/frontier/gpt-5.4.md
- forgecode/feedback/frontier/claude-opus-4.6.md
- hermes/feedback/frontier/claude-sonnet-feedback.md

Also created FEEDBACK_TEMPLATE.md as a style guide for all future feedback files.
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# Claude Opus 4.6 with ForgeCode - Feedback Report
**Model:** Claude Opus 4.6
**Size:** [Not specified]
**Provider:** Anthropic
**Harness:** ForgeCode
**Source References:** DEV Community (Liran Baba), ForgeCode Blog, Reddit r/ClaudeCode
**Date Compiled:** April 9, 2026
**Date Compiled:** April 9, 2026
**Source References:** DEV Community (Liran Baba), ForgeCode Blog, Reddit r/ClaudeCode
---
## Benchmark Performance
## Quick Reference
### TermBench 2.0 (Self-Reported via ForgeCode)
| Attribute | Value |
|-----------|-------|
| Model | Claude Opus 4.6 |
| Provider | Anthropic |
| Context Window | 200K tokens |
| Best For | Complex reasoning, large codebases, long-horizon tasks |
| Cost | ~$15/M input, ~$75/M output |
---
## Benchmark Results
### Terminal-Bench 2.0 (Harness-Specific)
- **Score:** 81.8% (tied for #1)
- **Comparison:** Claude Code + Opus 4.6 scored 58.0% (Rank #39)
- **Harness:** ForgeCode
- **Comparison:** Claude Code + Opus 4.6: 58.0% (Rank #39)
- **Gap:** ~24 percentage points in favor of ForgeCode harness
- **Note:** Score reflects harness+model combination, not raw model capability
### SWE-bench Verified (Independent - Princeton/UChicago)
### SWE-Bench Verified (Independent)
- **ForgeCode + Claude 4:** 72.7%
- **Claude Code + Claude 3.7 Sonnet (extended thinking):** 70.3%
- **Gap:** Only 2.4 percentage points
- **Gap:** Only 2.4 percentage points on independent validation
- **Source:** Princeton/UChicago
**Key Insight:** The benchmark gap narrows significantly on independent validation. TermBench 2.0 results are self-reported by ForgeCode itself.
### SWE-Bench Pro
- **Score:** 57.3% (Rank varies)
- **Behind:** Claude Mythos Preview (77.8%), GLM-5.1 (58.4%), GPT-5.4 (57.7%)
- **Source:** llm-stats.com
---
## Real-World Performance Feedback
### Speed
- **Observation:** "Noticeably faster than Claude Code. Not marginal, real."
- **Test Case:** Adding post counter to blog index (Astro 6, ~30 files)
- Claude Code: ~90 seconds
- ForgeCode + Opus 4.6: <30 seconds
- **Consistency:** Multi-file renames, component additions, layout restructuring all showed faster performance
### Why Faster
1. **Rust binary** vs Claude Code's TypeScript (better startup/memory)
2. **Context engine:** Indexes function signatures and module boundaries instead of dumping raw files (~90% context size reduction)
3. **Selective context:** Pulls only what the agent needs
### Stability
- **Assessment:** Excellent stability with Opus 4.6 through ForgeCode
- **No tool call failures reported** (unlike GPT 5.4 experience)
- Consistent performance across different task types
**Key Insight:** The benchmark gap narrows significantly on independent validation. Terminal-Bench results are self-reported by harness developers.
---
## What Worked Well
1. **Multi-file refactoring:** Handles complex changes across file boundaries efficiently
2. **Code comprehension:** Strong understanding of Astro/React components
3. **Speed on complex tasks:** Consistently 3x faster than Claude Code on identical tasks
4. **Planning with muse:** Plan output felt "more detailed and verbose than Claude Code's plan mode"
1. **Speed**
- **Observation:** "Noticeably faster than Claude Code. Not marginal, real."
- **Test Case:** Adding post counter to blog index (Astro 6, ~30 files)
- Claude Code: ~90 seconds
- ForgeCode + Opus 4.6: <30 seconds
- **Consistency:** Multi-file renames, component additions, layout restructuring all showed faster performance
- **Why:** Rust binary vs TypeScript, context engine indexes signatures (~90% size reduction), selective context
2. **Multi-file Refactoring**
- Handles complex changes across file boundaries efficiently
- Strong understanding of Astro/React components
- Consistently 3x faster than Claude Code on identical tasks
3. **Planning with Muse**
- Plan output felt "more detailed and verbose than Claude Code's plan mode"
4. **Stability**
- Excellent stability with Opus 4.6 through ForgeCode
- No tool call failures reported (unlike GPT 5.4 experience)
- Consistent performance across different task types
---
## Issues Encountered
1. **Ecosystem gaps:** No IDE extensions, no hooks, no checkpoints/rewind
2. **No auto-memory:** Context doesn't persist between sessions
3. **No built-in sandbox:** Requires manual `--sandbox` flag for isolation
1. **Ecosystem Gaps** (Major)
- **Description:** No IDE extensions, no hooks, no checkpoints/rewind
- **Impact:** Less integrated workflow compared to Claude Code
2. **No Auto-Memory** (Minor)
- **Description:** Context doesn't persist between sessions
- **Impact:** Requires re-contextualization on new sessions
3. **No Built-in Sandbox** (Minor)
- **Description:** Requires manual `--sandbox` flag for isolation
- **Impact:** Security requires explicit configuration
---
@@ -76,6 +100,11 @@
## Source References
1. **DEV Community:** https://dev.to/liran_baba/forgecode-vs-claude-code-which-ai-coding-agent-actually-wins-36c
2. **ForgeCode Blog:** https://forgecode.dev/blog/benchmarks-dont-matter/
3. **Reddit r/ClaudeCode:** https://www.reddit.com/r/ClaudeCode/comments/1royhni/someone_is_using_forgecodedev/
1. **DEV Community - ForgeCode vs Claude Code**: https://dev.to/liran_baba/forgecode-vs-claude-code-which-ai-coding-agent-actually-wins-36c
- Real-world performance comparison by Liran Baba
2. **ForgeCode Blog - Benchmarks Don't Matter**: https://forgecode.dev/blog/benchmarks-dont-matter/
- Documentation of harness optimizations and benchmark methodology
3. **Reddit r/ClaudeCode**: https://www.reddit.com/r/ClaudeCode/comments/1royhni/someone_is_using_forgecodedev/
- Community discussion on ForgeCode usage
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# GPT 5.4 with ForgeCode - Feedback Report
**Model:** GPT 5.4
**Size:** [Not specified]
**Provider:** OpenAI
**Harness:** ForgeCode
**Source References:** DEV Community (Liran Baba), ForgeCode Blog
**Date Compiled:** April 9, 2026
**Date Compiled:** April 9, 2026
**Source References:** DEV Community (Liran Baba), ForgeCode Blog
---
## Benchmark Performance
## Quick Reference
### TermBench 2.0 (Self-Reported via ForgeCode)
- **Score:** 81.8% (tied for #1 with Opus 4.6)
- **Note:** Achieved through extensive harness optimizations, not raw model capability
| Attribute | Value |
|-----------|-------|
| Model | GPT 5.4 |
| Provider | OpenAI |
| Context Window | 1M tokens |
| Best For | Terminal execution, speed |
| Cost | ~$10/M input, ~$30/M output |
---
## Real-World Performance Feedback
## Benchmark Results
### Stability Issues
- **Assessment:** "Borderline unusable" for some tasks
- **Specific Issue:** 15-minute research task on small repo
- Tool calls repeatedly failing
- Agent stuck in retry loops
- Required manual kill
### Terminal-Bench 2.0 (Harness-Specific)
- **Score:** 81.8% (tied for #1)
- **Harness:** ForgeCode
- **Date:** March 2026
- **Note:** Self-reported by ForgeCode; score reflects harness+model combination, not raw model capability
> "I asked it to research the architecture of a small repo. Fifteen minutes. Kept going unstable, tool calls failing, the agent retrying and spinning. I killed it."
### Tool Calling Reliability
- **Problem:** Persistent tool-call errors with GPT 5.4
- **ForgeCode Fixes Applied:**
1. Reordered JSON schema fields (`required` before `properties`)
2. Flattened nested schemas
3. Added explicit truncation reminders for partial file reads
- **Result:** These optimizations were benchmark-specific (described as "benchmaxxed")
### SWE-Bench Pro
- **Score:** 57.7% (Rank #3 overall)
- **Behind:** Claude Mythos Preview (77.8%), GLM-5.1 (58.4%)
- **Source:** llm-stats.com
---
## Harness Optimizations for GPT 5.4
## What Worked Well
From ForgeCode's "Benchmarks Don't Matter" blog series:
1. **Terminal Execution Speed**
- Fastest terminal execution among frontier models
- 47% token reduction with tool search
- Best price/performance ratio for terminal tasks
2. **Benchmark Performance**
- High scores on Terminal-Bench with ForgeCode harness optimizations
- Strong reasoning capabilities on AIME 2025, HMMT, GPQA-Diamond
---
## Issues Encountered
1. **Stability Problems** (Critical)
- **Description:** "Borderline unusable" for research tasks
- **Manifestation:** 15-minute research task on small repo failed repeatedly
- **Symptoms:** Tool calls failing, agent stuck in retry loops, required manual kill
- **Quote:** "I asked it to research the architecture of a small repo. Fifteen minutes. Kept going unstable, tool calls failing, the agent retrying and spinning. I killed it."
2. **Tool Calling Reliability** (Major)
- **Description:** Persistent tool-call errors with GPT 5.4
- **ForgeCode Fixes Applied:**
- Reordered JSON schema fields (`required` before `properties`)
- Flattened nested schemas
- Added explicit truncation reminders for partial file reads
- **Note:** These optimizations were benchmark-specific ("benchmaxxed")
3. **Long-Running Task Instability** (Major)
- **Description:** 15+ minute tasks became unstable
- **Impact:** Unpredictable failures requiring manual intervention
---
## Harness Optimizations
ForgeCode applied specific optimizations for GPT 5.4:
1. **Non-Interactive Mode:** System prompt rewritten to prohibit conversational branching
2. **Tool Naming:** Renaming edit tool arguments to `old_string` and `new_string` (names appearing frequently in training data) measurably dropped tool-call error rates
@@ -50,19 +84,11 @@ From ForgeCode's "Benchmarks Don't Matter" blog series:
---
## What Didn't Work Well
1. **Research tasks:** Tool calling failures causing infinite loops
2. **Long-running tasks:** 15+ minute tasks became unstable
3. **Consistency:** Unpredictable failures requiring manual intervention
---
## Comparison with Opus 4.6
## Comparison with Claude Opus 4.6
| Aspect | GPT 5.4 | Opus 4.6 |
|--------|---------|----------|
| TermBench 2.0 | 81.8% | 81.8% |
| Terminal-Bench 2.0 (ForgeCode) | 81.8% | 81.8% |
| Real-world stability | Poor | Excellent |
| Tool calling reliability | Problematic | Reliable |
| Research tasks | Unusable | Good |
@@ -73,5 +99,8 @@ From ForgeCode's "Benchmarks Don't Matter" blog series:
## Source References
1. **DEV Community:** https://dev.to/liran_baba/forgecode-vs-claude-code-which-ai-coding-agent-actually-wins-36c
2. **ForgeCode Blog:** https://forgecode.dev/blog/benchmarks-dont-matter/
1. **DEV Community - ForgeCode vs Claude Code**: https://dev.to/liran_baba/forgecode-vs-claude-code-which-ai-coding-agent-actually-wins-36c
- Real-world performance comparison by Liran Baba
2. **ForgeCode Blog - Benchmarks Don't Matter**: https://forgecode.dev/blog/benchmarks-dont-matter/
- Documentation of harness optimizations