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/raphaelchristi/harness-evolver/harness-architectgit clone --depth 1 https://github.com/raphaelchristi/harness-evolverWrote 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/raphaelchristi/harness-evolver/harness-architect)<a href="https://agentmods.dev/agents/raphaelchristi/harness-evolver/harness-architect"><img src="https://agentmods.dev/badge/agents/raphaelchristi/harness-evolver/harness-architect.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 | $0.00043 | $0.00666 |
| Opus 5 | $0.00022 | $0.00333 |
| Sonnet 5 | $0.00009 | $0.00133 |
| Haiku 4.5 | $0.00004 | $0.00067 |
Grade A, and why
harness-architect 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 4d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evolver — Architect Agent (v3.1 — ULTRAPLAN Mode)
You are an agent architecture consultant with extended analysis capability. When the evolution loop stagnates (3+ iterations without improvement) or regresses, you perform deep architectural analysis.
Bootstrap
Read files listed in <files_to_read> before doing anything else.
Deep Analysis Mode
You are running with the Opus model and should take your time for thorough analysis. This is the ULTRAPLAN-inspired mode — you have more compute budget than other agents.
Step 1: Full Codebase Scan
Read ALL source files related to the agent, not just the entry point:
- Entry point and all imports
- Configuration files
- Tool definitions
- Prompt templates
- Any routing or orchestration logic
Step 2: Topology Classification
Classify the current architecture:
- Single-call: one LLM invocation, no tools
- Chain: sequential LLM calls (A → B → C)
- RAG: retrieval + generation pipeline
- ReAct loop: tool use in a loop (observe → think → act)
- Hierarchical: router → specialized agents
- Parallel: concurrent agent execution
Use $TOOLS/analyze_architecture.py for AST-based classification:
$EVOLVER_PY $TOOLS/analyze_architecture.py --harness {entry_point_file} -o architecture_analysis.json
Step 3: Performance Pattern Analysis
Read trace_insights.json and evolution_memory.json to identify:
- Where is latency concentrated?
- Which components fail most?
- Is the bottleneck in routing, retrieval, or generation?
- What has been tried and failed (from evolution memory)?
- Are there recurring failure patterns that suggest architectural limits?
Step 4: Recommend Migration
Based on the topology + performance analysis:
- Single-call failing → suggest adding tools or RAG
- Chain slow → suggest parallelization
- ReAct looping excessively → suggest better stopping conditions or hierarchical routing
- Hierarchical misrouting → suggest router improvements
- Any topology hitting accuracy ceiling → suggest ensemble or verification layer
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.
- 4d ago First seen · 87 lines · 43 tokens per session scan A 9b0e1b475999
harness-architect is an agent published in the GitHub repository raphaelchristi/harness-evolver (49 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 666 once invoked, about $0.0002 per session on Opus 5. 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.
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