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 rules/poweroutlet2/openground/overviewgit clone --depth 1 https://github.com/poweroutlet2/opengroundWhat 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 | $0.00581 | $0.00581 |
| Opus 5 | $0.00291 | $0.00291 |
| Sonnet 5 | $0.00116 | $0.00116 |
| Haiku 4.5 | $0.00058 | $0.00058 |
Grade A, and why
overview 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 2d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Openground Project Configuration
Project Overview
Openground is a tool for extracting framework and library documentation from official sources (sitemaps and git repos) and making it queryable by AI coding agents. It consists of:
- RAG documentation ingestion pipeline: Extracts documentation from sources (sitemap.xml or git repos), stores pages as structured JSON, then chunks and embeds them into a local LanceDB database.
- MCP server: Exposes tools for AI agents to perform hybrid semantic and BM25 search over the documentation database.
The philosophy mandates simplicity of implementation for maintainers and ease of use for users.
Coding Style
- Paradigm: Functional programming preferred
- Type Hints: Required for all functions
- Error Handling: Errors must provide clear and actionable logging. Fail fast with actionable error messages.
- Documentation:
- Concise but informative docstrings for functions
- Prefer self-commenting code
- Inline comments only for particularly confusing lines
- Comments: Do not add comments that a human would not add. Do not add excessive comments. Do not add comments to parts of the code you are not working on.
Directory Structure
Openground is a RAG pipeline tool with CLI and MCP server components.
- Main modules:
cli.py,config.py,ingest.py,query.py,server.py,embeddings.py,console.py - extract/ subdirectory:
git.py,source.py,common.py,sitemap.py - Configuration: Managed via JSON config file (see
config.py) - Pipeline: extract → embed → query (hybrid semantic + BM25 search in lancedb)
Behavioral Rules
- Explanation: Explain "why" before coding
- File Size: No file size preference
- Comments: Only modify existing comments when touching related code
- Errors: Fail fast with actionable error messages
Project Commands
Development
uv run python ... # Run commands with venv
uv run ruff check . # Linting
uv run ty check . # Type checking
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.
- 2d ago First seen · 61 lines · 581 tokens per session scan A 216c2ffdb1f4
overview is a cursor rule published in the GitHub repository poweroutlet2/openground (54 stars, last pushed 5mo ago), licensed MIT. It adds 581 tokens to every session, about $0.0029 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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