Borrowing it
Nothing to install: this file belongs to colossus-lab/openarg_backend. 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/colossus-lab/openarg_backend/main/CLAUDE.mdgit clone --depth 1 https://github.com/colossus-lab/openarg_backendWrote 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/colossus-lab/openarg_backend/claude-md)<a href="https://agentmods.dev/instructions/colossus-lab/openarg_backend/claude-md"><img src="https://agentmods.dev/badge/instructions/colossus-lab/openarg_backend/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/colossus-lab/openarg_backend/claude-md"><img src="https://agentmods.dev/badge/instructions/colossus-lab/openarg_backend/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 | $0.05787 | $0.05787 |
| Opus 5.5 | $0.02315 | $0.02315 |
| Sonnet 5.5 | $0.01157 | $0.01157 |
| Haiku 4.5 | $0.00579 | $0.00579 |
Grade A, and why
openarg_backend 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 29d 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 — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenArg Backend
Backend service for OpenArg — AI-powered analysis of Argentine government open data. It scrapes public data portals into PostgreSQL, embeds the catalogue, keeps curated marts and live connectors, and answers natural-language questions for the web chat (/api/v1/query/*), the public API (/api/v1/ask) and the public MCP (mcp_publico/, mcp.openarg.org). See README.md for the full picture.
Stack
- Framework: FastAPI 0.115 + Uvicorn (async, UVLoop)
- Database: PostgreSQL 16 + pgvector (HNSW indexing, 1024-dim embeddings) + PostGIS (migration 0025)
- ORM: SQLAlchemy 2.0 (async) + Alembic migrations
- DI: Dishka 1.6 (IoC container)
- Workers: Celery 5.4 + Redis 7 (broker + cache + results)
- Answer engines (chosen per turn with
ANSWERS_ENGINE, code defaultlegacy;application/answers/engine.py):agent: Claude Sonnet 4.6 on AWS Bedrock (BEDROCK_AGENT_MODEL) in a tool loop, through the Anthropic SDK (AsyncAnthropicBedrock). The agent has answered in prod since 2026-10-03.legacy: the LangGraph graph on Claude Haiku 4.5 on Bedrock (BEDROCK_LLM_MODEL) with Google Gemini (GEMINI_MODEL, default 2.5 Flash) as fallback. Haiku 4.5 is also the default model of the workers' LLM tasks.
- Figure verifier:
ANSWERS_VERIFY_MODE=off/shadow(default) /correct(application/answers/verification.py) - Embeddings: AWS Bedrock Cohere Embed Multilingual v3 (1024-dim)
- AWS credentials: boto3's default chain (instance role on the servers); no keys required in
.env - HTTP: HTTPX (async client)
- Auth: shared service key (
X-API-Key) + Google ID token for the frontend;oarg_sk_user keys (Bearer) for the public API/MCP;X-Admin-Keyfor/admin - Rate Limiting: SlowAPI + Redis counters (monthly quotas in
application/public_quota.pyandapplication/web_quota.py) - Config: TOML files + Pydantic settings
- Logging: structlog
Architecture (Hexagonal / Ports & Adapters)
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.
- 29d ago Changed · +74 lines · +2,150 tokens per session d8d80c182f41
- 2mo ago First seen · 269 lines · 3,637 tokens per session scan A d679bebba94f
openarg_backend CLAUDE.md is an instructions file published in the GitHub repository colossus-lab/openarg_backend (150 stars, last pushed 3d ago), licensed MIT. It adds 5,787 tokens to every session, about $0.0231 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 2026-08-30.
openarg_backend CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| openarg_backend CLAUDE.mdcolossus-lab/openarg_backend | Instructions file | 150 | 3d ago | MIT | A | 5,787 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
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| 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 |