Borrowing it
Nothing to install: this file belongs to yasinyaman/fusion. 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/yasinyaman/fusion/master/CLAUDE.mdgit clone --depth 1 https://github.com/yasinyaman/fusionWrote 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/yasinyaman/fusion/claude-md)<a href="https://agentmods.dev/instructions/yasinyaman/fusion/claude-md"><img src="https://agentmods.dev/badge/instructions/yasinyaman/fusion/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/yasinyaman/fusion/claude-md"><img src="https://agentmods.dev/badge/instructions/yasinyaman/fusion/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 | $0.02598 | $0.02598 |
| Opus 5.5 | $0.01039 | $0.01039 |
| Sonnet 5.5 | $0.00520 | $0.00520 |
| Haiku 4.5 | $0.00260 | $0.00260 |
Grade A, and why
fusion 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 1mo 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fusion OLAP Engine
DuckDB-powered in-memory analytics engine — LLM tool for data access via MCP, REST API, and the Python SDK. Hexagonal (ports & adapters) architecture since 1.0.0.
Project Overview
- Language: Python 3.12+ (CI: 3.12 / 3.13 / 3.14)
- Version: 1.1.0 (smart transfer: slices, streaming ingest, semi-joins, incremental refresh)
- Core dependencies: DuckDB 1.5+, pyarrow, requests, sqlglot 30 (pandas is an optional extra)
- Data source: Warp REST API (PostgreSQL/MySQL)
- Tooling: uv (
uv.lockis committed), ruff, mypy 2, pytest 9
Commands
- Install:
uv sync --all-extras - Test:
uv run pytest(coverage gatefail_under = 80) - Lint:
uv run ruff check fusion tests demoanduv run ruff format --check fusion tests demo - Types:
uv run mypy fusion(strict flags ondomain,ports,application) - Lock check:
uv lock --check - Demo:
uv run python -m demo.demo --scale 0.1 - MCP server:
uv run fusion-mcp --warp-url http://localhost:8000 --database mydb - REST server:
uv run fusion-rest --warp-url http://localhost:8000 --auto-discover --port 9000
Always validate with uv run --frozen ...; the locked tool versions are newer than typical system installs.
Architecture
inbound adapters (REST, MCP, CLI, SDK) ──► application (FusionApp + services) ──► ports (Protocols)
│ ▲
▼ │ implemented by
domain (pure Python) outbound adapters (DuckDB, sqlglot,
memory cache, scheduler, Warp)
fusion.bootstrap.build_app(settings) wires adapters into the services.
Dependency rule (enforced by tests/architecture/test_dependency_rules.py, which walks every import including lazy ones):
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.
- 1mo ago Changed · +12 lines · +468 tokens per session 41eaaeb5a2f3
- 1mo ago Changed · +18 lines · +952 tokens per session 666def644098
- 2mo ago First seen · 102 lines · 1,178 tokens per session scan A 734484c3ea6e
fusion CLAUDE.md is an instructions file published in the GitHub repository yasinyaman/fusion (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 2,598 tokens to every session, about $0.0104 per session on Opus 5.5. 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.
fusion CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| fusion CLAUDE.mdyasinyaman/fusion | Instructions file | 2 | 1mo ago | Apache-2.0 | A | 2,598 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |