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.
git clone --depth 1 https://github.com/coeusyk/inference-xWrote 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/rules/coeusyk/inference-x/project)<a href="https://agentmods.dev/rules/coeusyk/inference-x/project"><img src="https://agentmods.dev/badge/rules/coeusyk/inference-x/project/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/rules/coeusyk/inference-x/project"><img src="https://agentmods.dev/badge/rules/coeusyk/inference-x/project.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 | $0.00653 | $0.00653 |
| Opus 5.5 | $0.00261 | $0.00261 |
| Sonnet 5.5 | $0.00131 | $0.00131 |
| Haiku 4.5 | $0.00065 | $0.00065 |
Grade A, and why
project 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
InferenceX project rules
- Treat InferenceX as a backend-first, layered LLM inference platform.
- Preserve stable public API contracts once introduced.
- Add new capabilities by adding modules, not by rewriting unrelated files.
- Keep route handlers thin; put business logic in services.
- Use typed schemas for requests, responses, and internal DTOs.
- Prefer dependency injection over direct global imports.
- Make behavior config-driven where possible, especially for models, routing, and logging.
- Do not begin UI-heavy work before backend phase goals are complete.
- When architecture changes, update
docs/ARCHITECTURE.md,docs/PHASES.md, and any affected OpenSpec change docs in the same task. - Favor incremental edits that preserve previous working behavior.
Repo boundaries
src/inference_x/api/exposes HTTP endpoints and request validation.src/inference_x/services/orchestrates application logic.src/inference_x/engines/contains inference engine interfaces and implementations.src/inference_x/routing/contains model selection logic and policies.src/inference_x/observability/contains middleware, metrics, and exporters.src/inference_x/schemas/contains Pydantic models only.config/stores YAML configuration files; avoid hardcoding deploy-specific values.
Path Handling
- Never use absolute paths anywhere in generated code, config files, scripts, or documentation.
- This project runs on different machines (Windows WSL2, Linux) where home directories and project roots differ. An absolute path that works on one machine will silently break on another.
- Always use paths relative to the project root or the file being edited.
- For Python code, resolve paths at runtime using
Path(__file__).parentorPath(__file__).resolve().parentanchored to a known file in the module tree. - For config files (YAML, TOML), use relative paths from the config file's own location,
or use a placeholder like
./models/that the application resolves at startup. - For shell scripts and the Makefile, use
$(shell pwd)or$(CURDIR)— never hardcode a path like/home/user/or/mnt/c/. - If a path must be configurable (e.g., model weights directory), expose it as an environment variable with a sensible relative default, not a hardcoded absolute path.
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 First seen · 53 lines · 653 tokens per session scan A bd05881887c6
project is a cursor rule published in the GitHub repository coeusyk/inference-x (2 stars, last pushed 19d ago), licensed MIT. It adds 653 tokens to every session, about $0.0026 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.
Other cursor rules, from other repositories
go-api-handlers
Use authorization functions for apps.
use-frontend-api-client
Generated API client usage.
fastapi-pydantic
You are an expert in Python, FastAPI, and scalable API development.
backend
You are an expert in Go, Gin, Gorm, Gen, Cosy (https://cosy.uozi.org/) with a deep understanding of best practices and performance optimization techniques in these technologies.
python
Python best practices and patterns for modern software development with Flask and SQLite.
django
Definitive guidelines for writing maintainable, performant, and secure Django applications, emphasizing modern best practices, clear code organization, and efficient patterns.