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/ifokeev/telegram-ai-agent/cursorrulesgit clone --depth 1 https://github.com/ifokeev/telegram-ai-agentWhat 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 | $0.00423 | $0.00423 |
| Opus 5 | $0.00211 | $0.00211 |
| Sonnet 5 | $0.00085 | $0.00085 |
| Haiku 4.5 | $0.00042 | $0.00042 |
Grade A, and why
cursorrules 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 46 lines · 423 tokens per session scan A 5ee6ed079959
cursorrules is a cursor rule published in the GitHub repository ifokeev/telegram-ai-agent (42 stars, last pushed 1y ago), with no licence file. It adds 423 tokens to every session, about $0.0021 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.
Other cursor rules, from other repositories
telegram-bot-api
API actions, features, and options for Telegram Bot library.
ktnip-ksp-tests
KSP processor test conventions for ktnip.
telegram-bot-types
Options, types, and serialization for Telegram Bot library.
telegram-bot-tests
Test conventions for Telegram Bot library.
architecture
这是一个把 Telegram 消息导入、导出到数据库中并提供搜索的服务。支持向量搜索和语义匹配，基于 OpenAI 的语义向量技术。.
events
When adding a new event, ensure all of the following are updated in one change.