Borrowing it
Nothing to install: this file belongs to deepanshu2711/AI-System-Design-Consultant. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/deepanshu2711/AI-System-Design-Consultant/main/CLAUDE.mdgit clone --depth 1 https://github.com/deepanshu2711/AI-System-Design-ConsultantWrote 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/instructions/deepanshu2711/ai-system-design-consultant/claude-md)<a href="https://agentmods.dev/instructions/deepanshu2711/ai-system-design-consultant/claude-md"><img src="https://agentmods.dev/badge/instructions/deepanshu2711/ai-system-design-consultant/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/deepanshu2711/ai-system-design-consultant/claude-md"><img src="https://agentmods.dev/badge/instructions/deepanshu2711/ai-system-design-consultant/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00674 | $0.00674 |
| Opus 5 | $0.00337 | $0.00337 |
| Sonnet 5 | $0.00135 | $0.00135 |
| Haiku 4.5 | $0.00067 | $0.00067 |
Grade A, and why
AI-System-Design-Consultant CLAUDE.md 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 10d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
What this is
A FastAPI + LangGraph multi-agent system that conducts an automated system-design "interview": a supervisor node routes a shared DesignState through specialist LLM agents (clarifying questions, requirement analysis, traffic estimation, capacity planning, database/cache/queue/CDN/storage/API design), each emitting a Pydantic-typed design artifact. All agents share one local Ollama model via langchain-ollama.
Running it
uv run fastapi dev app/main.py
Requires a local Ollama daemon running with qwen2.5:3b pulled — the model is hardcoded in app/utils/llm_factory.py (no env var override). There is no Docker setup; Ollama must be installed and running on the dev machine.
Endpoints: POST /design/start kicks off a new graph run; POST /design/resume resumes an interrupted run (human-in-the-loop clarification) via LangGraph's Command(resume=...). Checkpointing is in-memory (MemorySaver) only — state does not survive a process restart.
Load-bearing typos — do not "fix" these paths
app/grpahs/supervisor_graph.py(notgraphs)app/state/desgin_state.py(notdesign_state)
These misspellings are intentional-for-now and other code imports from these exact paths. Renaming them will break imports across the codebase.
Agent node pattern
Every file in app/agents/ follows the same shape: build messages → bind tools → tool-call loop capped by MAX_TOOL_ITERATIONS → force final structured output → return Command(goto="supervisor", update={...}). The supervisor (app/agents/supervisor.py) is the sole router; agents never call each other directly. System prompts live in app/prompts/<agent_name>/v1.py (versioned per agent — bump to v2.py etc. rather than editing v1 in place if iterating on a prompt). Tools shared across agents live in app/tools/ (calculator.py, json_formatter.py).
Current WIP state
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.
- 10d ago First seen · 39 lines · 674 tokens per session scan A d33b70af4b02
AI-System-Design-Consultant CLAUDE.md is an instructions file published in the GitHub repository deepanshu2711/AI-System-Design-Consultant (2 stars, last pushed 7d ago), licensed MIT. It adds 674 tokens to every session, about $0.0034 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 2026-08-31.
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