LoopX is a provider-neutral control plane that gives long-running AI-agent work persistent state, decisions, governance, recovery, and handoffs across different agent harnesses. It is for managing and reviewing durable work performed by Codex, Claude Code, Cursor, dsh, or custom agent systems.
Borrowing it
Nothing to install: this file belongs to huangruiteng/loopx. 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/huangruiteng/loopx/main/AGENTS.mdgit clone --depth 1 https://github.com/huangruiteng/loopxWrote 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/huangruiteng/loopx/agents-md)<a href="https://agentmods.dev/instructions/huangruiteng/loopx/agents-md"><img src="https://agentmods.dev/badge/instructions/huangruiteng/loopx/agents-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/huangruiteng/loopx/agents-md"><img src="https://agentmods.dev/badge/instructions/huangruiteng/loopx/agents-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 | $0.06412 | $0.06412 |
| Opus 5.5 | $0.02565 | $0.02565 |
| Sonnet 5.5 | $0.01282 | $0.01282 |
| Haiku 4.5 | $0.00641 | $0.00641 |
Grade A, and why
loopx AGENTS.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 — 555 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions
Goal-Oriented Development
Before selecting non-trivial work, resolve the current requested outcome from
user direction, the linked issue/task, accepted contract or demonstrated bug.
For cross-cutting LoopX work, consult the overall roadmap
and relevant domain acceptance; do not make every fix wait for every RFC or
invent a roadmap id. Check latest main, related PRs and canonical Todos so an
older task description cannot override corrected direction or duplicate work.
Carry one compact delivery brief from task to PR: goal/source, current gap, observable result, owning boundary and decisive acceptance evidence. Reuse the existing task/PR fields; keep private Goal state out of public artifacts. Choose a complete, independently reviewable and reversible outcome slice. Small diffs, fields, receipts, test counts and merged PR counts do not establish progress. Characterization, prerequisites, research, docs and maintenance are valid when they remove an evidenced gap or enable a named real next step.
Continue through the selected slice's implementation, integration, negative cases and readback while authorized work remains feasible. Do not stop after setup, a serializer, a mock or an isolated smoke when the useful outcome is still missing. Do not expand scope merely to make a PR larger. When a staged boundary is necessary, name the delivered delta, remaining gap, next owner/ dependency and why the boundary improves verification or rollback. Reuse or update an existing successor; do not create ceremonial follow-up tasks for a completed request. Real authorization, cost and operational stop gates remain.
For multi-Agent changes, qualify the relationship the user needs: dependency artifacts, receiver adoption, claim/lease handling, independent acceptance and result return as applicable. Sending a message or registering workers does not prove collaboration. Missing frontend/Lark/CLI companion work makes a product journey partial even when a backend slice is ready to merge.
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 · +12 lines · +144 tokens per session 6d97ed267c51
- 1mo ago Changed · +81 lines · +1,075 tokens per session f79992f46f44
- 1mo ago Changed · +14 lines · +138 tokens per session 3bd835de97f9
- 1mo ago Changed · +13 lines · +156 tokens per session f27615568a35
- 1mo ago Changed · +3 lines · +45 tokens per session bf466114cf5d
- 1mo ago First seen · 432 lines · 4,854 tokens per session scan A 5728ac419b7e
loopx AGENTS.md is an instructions file published in the GitHub repository huangruiteng/loopx (6,356 stars, last pushed today), licensed Apache-2.0. It adds 6,412 tokens to every session, about $0.0256 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.
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